---
license: mit
library_name: sklearn
tags:
- sklearn
- skops
- tabular-classification
model_format: pickle
model_file: model.pkl
widget:
  structuredData:
    BsmtFinSF1:
    - 1280
    - 1464
    - 0
    BsmtUnfSF:
    - 402
    - 536
    - 795
    Condition2:
    - Norm
    - Norm
    - Norm
    ExterQual:
    - Ex
    - Gd
    - Gd
    Foundation:
    - PConc
    - PConc
    - PConc
    GarageCars:
    - 3
    - 3
    - 1
    GarageType:
    - BuiltIn
    - Attchd
    - Detchd
    Heating:
    - GasA
    - GasA
    - GasA
    HeatingQC:
    - Ex
    - Ex
    - TA
    HouseStyle:
    - 2Story
    - 1Story
    - 2.5Fin
    MSSubClass:
    - 60
    - 20
    - 75
    MasVnrArea:
    - 272.0
    - 246.0
    - 0.0
    MasVnrType:
    - Stone
    - Stone
    - .nan
    MiscFeature:
    - .nan
    - .nan
    - .nan
    MoSold:
    - 8
    - 7
    - 3
    OverallQual:
    - 10
    - 8
    - 4
    Street:
    - Pave
    - Pave
    - Pave
    TotalBsmtSF:
    - 1682
    - 2000
    - 795
    YearRemodAdd:
    - 2008
    - 2005
    - 1950
    YrSold:
    - 2008
    - 2007
    - 2006
---

# Model description

This is a Lasso regression model trained on ames housing dataset from OpenML

## Intended uses & limitations

This model is not ready to be used in production.

## Training Procedure

[More Information Needed]

### Hyperparameters

<details>
<summary> Click to expand </summary>

| Hyperparameter                                                  | Value                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
|-----------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| memory                                                          |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| steps                                                           | [('columntransformer', ColumnTransformer(transformers=[('pipeline',<br />                                 Pipeline(steps=[('standardscaler',<br />                                                  StandardScaler()),<br />                                                 ('simpleimputer',<br />                                                  SimpleImputer(add_indicator=True))]),<br />                                 <sklearn.compose._column_transformer.make_column_selector object at 0x000001CF5D97B7C0>),<br />                                ('onehotencoder',<br />                                 OneHotEncoder(handle_unknown='ignore'),<br />                                 <sklearn.compose._column_transformer.make_column_selector object at 0x000001CF128511E0>)])), ('lassocv', LassoCV())] |
| verbose                                                         | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
| columntransformer                                               | ColumnTransformer(transformers=[('pipeline',<br />                                 Pipeline(steps=[('standardscaler',<br />                                                  StandardScaler()),<br />                                                 ('simpleimputer',<br />                                                  SimpleImputer(add_indicator=True))]),<br />                                 <sklearn.compose._column_transformer.make_column_selector object at 0x000001CF5D97B7C0>),<br />                                ('onehotencoder',<br />                                 OneHotEncoder(handle_unknown='ignore'),<br />                                 <sklearn.compose._column_transformer.make_column_selector object at 0x000001CF128511E0>)])                                                  |
| lassocv                                                         | LassoCV()                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| columntransformer__n_jobs                                       |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| columntransformer__remainder                                    | drop                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| columntransformer__sparse_threshold                             | 0.3                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
| columntransformer__transformer_weights                          |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| columntransformer__transformers                                 | [('pipeline', Pipeline(steps=[('standardscaler', StandardScaler()),<br />                ('simpleimputer', SimpleImputer(add_indicator=True))]), <sklearn.compose._column_transformer.make_column_selector object at 0x000001CF5D97B7C0>), ('onehotencoder', OneHotEncoder(handle_unknown='ignore'), <sklearn.compose._column_transformer.make_column_selector object at 0x000001CF128511E0>)]                                                                                                                                                                                                                                                                                                                                                                                           |
| columntransformer__verbose                                      | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
| columntransformer__verbose_feature_names_out                    | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| columntransformer__pipeline                                     | Pipeline(steps=[('standardscaler', StandardScaler()),<br />                ('simpleimputer', SimpleImputer(add_indicator=True))])                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
| columntransformer__onehotencoder                                | OneHotEncoder(handle_unknown='ignore')                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| columntransformer__pipeline__memory                             |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| columntransformer__pipeline__steps                              | [('standardscaler', StandardScaler()), ('simpleimputer', SimpleImputer(add_indicator=True))]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
| columntransformer__pipeline__verbose                            | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
| columntransformer__pipeline__standardscaler                     | StandardScaler()                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
| columntransformer__pipeline__simpleimputer                      | SimpleImputer(add_indicator=True)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
| columntransformer__pipeline__standardscaler__copy               | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| columntransformer__pipeline__standardscaler__with_mean          | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| columntransformer__pipeline__standardscaler__with_std           | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| columntransformer__pipeline__simpleimputer__add_indicator       | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| columntransformer__pipeline__simpleimputer__copy                | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| columntransformer__pipeline__simpleimputer__fill_value          |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| columntransformer__pipeline__simpleimputer__keep_empty_features | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
| columntransformer__pipeline__simpleimputer__missing_values      | nan                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
| columntransformer__pipeline__simpleimputer__strategy            | mean                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| columntransformer__pipeline__simpleimputer__verbose             | deprecated                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| columntransformer__onehotencoder__categories                    | auto                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| columntransformer__onehotencoder__drop                          |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| columntransformer__onehotencoder__dtype                         | <class 'numpy.float64'>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
| columntransformer__onehotencoder__handle_unknown                | ignore                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| columntransformer__onehotencoder__max_categories                |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| columntransformer__onehotencoder__min_frequency                 |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| columntransformer__onehotencoder__sparse                        | deprecated                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| columntransformer__onehotencoder__sparse_output                 | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| lassocv__alphas                                                 |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| lassocv__copy_X                                                 | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| lassocv__cv                                                     |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| lassocv__eps                                                    | 0.001                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
| lassocv__fit_intercept                                          | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| lassocv__max_iter                                               | 1000                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| lassocv__n_alphas                                               | 100                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
| lassocv__n_jobs                                                 |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| lassocv__positive                                               | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
| lassocv__precompute                                             | auto                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| lassocv__random_state                                           |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| lassocv__selection                                              | cyclic                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| lassocv__tol                                                    | 0.0001                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| lassocv__verbose                                                | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |

</details>

### Model Plot

<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-1" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,ColumnTransformer(transformers=[(&#x27;pipeline&#x27;,Pipeline(steps=[(&#x27;standardscaler&#x27;,StandardScaler()),(&#x27;simpleimputer&#x27;,SimpleImputer(add_indicator=True))]),&lt;sklearn.compose._column_transformer.make_column_selector object at 0x000001CF5D97B7C0&gt;),(&#x27;onehotencoder&#x27;,OneHotEncoder(handle_unknown=&#x27;ignore&#x27;),&lt;sklearn.compose._column_transformer.make_column_selector object at 0x000001CF128511E0&gt;)])),(&#x27;lassocv&#x27;, LassoCV())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-1" type="checkbox" ><label for="sk-estimator-id-1" class="sk-toggleable__label sk-toggleable__label-arrow">Pipeline</label><div class="sk-toggleable__content"><pre>Pipeline(steps=[(&#x27;columntransformer&#x27;,ColumnTransformer(transformers=[(&#x27;pipeline&#x27;,Pipeline(steps=[(&#x27;standardscaler&#x27;,StandardScaler()),(&#x27;simpleimputer&#x27;,SimpleImputer(add_indicator=True))]),&lt;sklearn.compose._column_transformer.make_column_selector object at 0x000001CF5D97B7C0&gt;),(&#x27;onehotencoder&#x27;,OneHotEncoder(handle_unknown=&#x27;ignore&#x27;),&lt;sklearn.compose._column_transformer.make_column_selector object at 0x000001CF128511E0&gt;)])),(&#x27;lassocv&#x27;, LassoCV())])</pre></div></div></div><div class="sk-serial"><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" ><label for="sk-estimator-id-2" class="sk-toggleable__label sk-toggleable__label-arrow">columntransformer: ColumnTransformer</label><div class="sk-toggleable__content"><pre>ColumnTransformer(transformers=[(&#x27;pipeline&#x27;,Pipeline(steps=[(&#x27;standardscaler&#x27;,StandardScaler()),(&#x27;simpleimputer&#x27;,SimpleImputer(add_indicator=True))]),&lt;sklearn.compose._column_transformer.make_column_selector object at 0x000001CF5D97B7C0&gt;),(&#x27;onehotencoder&#x27;,OneHotEncoder(handle_unknown=&#x27;ignore&#x27;),&lt;sklearn.compose._column_transformer.make_column_selector object at 0x000001CF128511E0&gt;)])</pre></div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-3" type="checkbox" ><label for="sk-estimator-id-3" class="sk-toggleable__label sk-toggleable__label-arrow">pipeline</label><div class="sk-toggleable__content"><pre>&lt;sklearn.compose._column_transformer.make_column_selector object at 0x000001CF5D97B7C0&gt;</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-4" type="checkbox" ><label for="sk-estimator-id-4" class="sk-toggleable__label sk-toggleable__label-arrow">StandardScaler</label><div class="sk-toggleable__content"><pre>StandardScaler()</pre></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-5" type="checkbox" ><label for="sk-estimator-id-5" class="sk-toggleable__label sk-toggleable__label-arrow">SimpleImputer</label><div class="sk-toggleable__content"><pre>SimpleImputer(add_indicator=True)</pre></div></div></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-6" type="checkbox" ><label for="sk-estimator-id-6" class="sk-toggleable__label sk-toggleable__label-arrow">onehotencoder</label><div class="sk-toggleable__content"><pre>&lt;sklearn.compose._column_transformer.make_column_selector object at 0x000001CF128511E0&gt;</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-7" type="checkbox" ><label for="sk-estimator-id-7" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)</pre></div></div></div></div></div></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-8" type="checkbox" ><label for="sk-estimator-id-8" class="sk-toggleable__label sk-toggleable__label-arrow">LassoCV</label><div class="sk-toggleable__content"><pre>LassoCV()</pre></div></div></div></div></div></div></div>

## Evaluation Results

| Metric   |    Value |
|----------|----------|
| R2 score | 0.753308 |
| MAE      | 0.112742 |

# How to Get Started with the Model

Use the following code to get started:

```python
import joblib
from skops.hub_utils import download
import json
import pandas as pd
download(repo_id="haizad/ames-housing-lasso-predictor", dst='ames-housing-lasso-predictor')
pipeline = joblib.load( "ames-housing-lasso-predictor/model.pkl")
with open("ames-housing-lasso-predictor/config.json") as f:
    config = json.load(f)
pipeline.predict(pd.DataFrame.from_dict(config["sklearn"]["example_input"]))
```

# Model Card Authors

This model card is written by following authors:

[More Information Needed]

# Model Card Contact

You can contact the model card authors through following channels:
[More Information Needed]

# Citation

Below you can find information related to citation.

**BibTeX:**
```
[More Information Needed]
```

# Evaluation

![evaluation](prediction_error.png)