---
license: mit
library_name: sklearn
tags:
- sklearn
- skops
- tabular-regression
widget:
structuredData:
Height:
- 11.52
- 12.48
- 12.3778
Length1:
- 23.2
- 24.0
- 23.9
Length2:
- 25.4
- 26.3
- 26.5
Length3:
- 30.0
- 31.2
- 31.1
Species:
- Bream
- Bream
- Bream
Width:
- 4.02
- 4.3056
- 4.6961
---
# Model description
This is a GradientBoostingRegressor on a fish dataset.
## Intended uses & limitations
This model is intended for educational purposes.
### Hyperparameters
The model is trained with below hyperparameters.
Click to expand
| Hyperparameter | Value |
|-----------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| memory | |
| steps | [('columntransformer', ColumnTransformer(remainder='passthrough',transformers=[('onehotencoder',OneHotEncoder(handle_unknown='ignore',sparse=False),
Pipeline(steps=[('columntransformer',ColumnTransformer(remainder='passthrough',transformers=[('onehotencoder',OneHotEncoder(handle_unknown='ignore',sparse=False),<sklearn.compose._column_transformer.make_column_selector object at 0x000001E750BBC6A0>)])),('gradientboostingregressor',GradientBoostingRegressor(random_state=42))])Please rerun this cell to show the HTML repr or trust the notebook.
Pipeline(steps=[('columntransformer',ColumnTransformer(remainder='passthrough',transformers=[('onehotencoder',OneHotEncoder(handle_unknown='ignore',sparse=False),<sklearn.compose._column_transformer.make_column_selector object at 0x000001E750BBC6A0>)])),('gradientboostingregressor',GradientBoostingRegressor(random_state=42))])
ColumnTransformer(remainder='passthrough',transformers=[('onehotencoder',OneHotEncoder(handle_unknown='ignore',sparse=False),<sklearn.compose._column_transformer.make_column_selector object at 0x000001E750BBC6A0>)])
<sklearn.compose._column_transformer.make_column_selector object at 0x000001E750BBC6A0>
OneHotEncoder(handle_unknown='ignore', sparse=False)
['Length1', 'Length2', 'Length3', 'Height', 'Width']
passthrough
GradientBoostingRegressor(random_state=42)