Add scikit-learn-intelex KNN model example
Browse files- README.md +136 -0
- config.json +108 -0
- model-optimized.pkl +3 -0
README.md
ADDED
@@ -0,0 +1,136 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: sklearn
|
3 |
+
tags:
|
4 |
+
- sklearn
|
5 |
+
- skops
|
6 |
+
- tabular-classification
|
7 |
+
- scikit-learn-intelex
|
8 |
+
model_format: pickle
|
9 |
+
model_file: model-optimized.pkl
|
10 |
+
widget:
|
11 |
+
structuredData:
|
12 |
+
x0:
|
13 |
+
- -2.91869894329896
|
14 |
+
- 1.2861311367611363
|
15 |
+
- -0.17676780746347887
|
16 |
+
x1:
|
17 |
+
- 4.378017491251676
|
18 |
+
- -3.150744413325807
|
19 |
+
- -3.268596999474564
|
20 |
+
x10:
|
21 |
+
- 0.8047174523586147
|
22 |
+
- -1.2969581776011339
|
23 |
+
- 0.31762144434782824
|
24 |
+
x11:
|
25 |
+
- -3.2390344195350487
|
26 |
+
- 1.1959946004673214
|
27 |
+
- 0.7563114595834011
|
28 |
+
x12:
|
29 |
+
- -0.5746008540164298
|
30 |
+
- 3.3486745844798804
|
31 |
+
- 2.948767259442758
|
32 |
+
x13:
|
33 |
+
- 3.5915430703361673
|
34 |
+
- 3.5265729573580655
|
35 |
+
- 0.015963649217312414
|
36 |
+
x14:
|
37 |
+
- 0.8137258237766396
|
38 |
+
- -3.6846723813183138
|
39 |
+
- -0.0726270826536789
|
40 |
+
x2:
|
41 |
+
- 1.660608706929798
|
42 |
+
- -2.915945269906298
|
43 |
+
- -0.2966018717870358
|
44 |
+
x3:
|
45 |
+
- 5.717843051082721
|
46 |
+
- 0.6565179693281937
|
47 |
+
- 3.2575477536637036
|
48 |
+
x4:
|
49 |
+
- -1.319254071176227
|
50 |
+
- 3.2948523559028287
|
51 |
+
- 1.5435232801320602
|
52 |
+
x5:
|
53 |
+
- -2.9780546324477646
|
54 |
+
- -1.3618488406102902
|
55 |
+
- 1.5867699986090962
|
56 |
+
x6:
|
57 |
+
- 1.6471024314152358
|
58 |
+
- 1.3658191827488237
|
59 |
+
- -1.4529064414158699
|
60 |
+
x7:
|
61 |
+
- 0.3525021389263907
|
62 |
+
- 1.3302365122960365
|
63 |
+
- 0.09438131139298833
|
64 |
+
x8:
|
65 |
+
- -0.44858117376143913
|
66 |
+
- 0.9049016837557153
|
67 |
+
- 2.195212749960551
|
68 |
+
x9:
|
69 |
+
- 0.5394501179095126
|
70 |
+
- -2.85779169799503
|
71 |
+
- 1.3981326527555564
|
72 |
+
---
|
73 |
+
|
74 |
+
# Model description
|
75 |
+
|
76 |
+
[More Information Needed]
|
77 |
+
|
78 |
+
## Intended uses & limitations
|
79 |
+
|
80 |
+
[More Information Needed]
|
81 |
+
|
82 |
+
## Training Procedure
|
83 |
+
|
84 |
+
### Hyperparameters
|
85 |
+
|
86 |
+
The model is trained with below hyperparameters.
|
87 |
+
|
88 |
+
<details>
|
89 |
+
<summary> Click to expand </summary>
|
90 |
+
|
91 |
+
| Hyperparameter | Value |
|
92 |
+
|------------------|-----------|
|
93 |
+
| algorithm | auto |
|
94 |
+
| leaf_size | 30 |
|
95 |
+
| metric | minkowski |
|
96 |
+
| metric_params | |
|
97 |
+
| n_jobs | |
|
98 |
+
| n_neighbors | 3 |
|
99 |
+
| p | 2 |
|
100 |
+
| weights | uniform |
|
101 |
+
|
102 |
+
</details>
|
103 |
+
|
104 |
+
### Model Plot
|
105 |
+
|
106 |
+
The model plot is below.
|
107 |
+
|
108 |
+
<style>#sk-container-id-4 {color: black;background-color: white;}#sk-container-id-4 pre{padding: 0;}#sk-container-id-4 div.sk-toggleable {background-color: white;}#sk-container-id-4 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-4 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-4 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-4 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-4 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 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-4 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-4 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-4 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 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-4 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-4 div.sk-item {position: relative;z-index: 1;}#sk-container-id-4 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-4 div.sk-item::before, #sk-container-id-4 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-4 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-4 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-4 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-4 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-4 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-4 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-4 div.sk-label-container {text-align: center;}#sk-container-id-4 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-4 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-4" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>KNeighborsClassifier(n_neighbors=3)</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"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-4" type="checkbox" checked><label for="sk-estimator-id-4" class="sk-toggleable__label sk-toggleable__label-arrow">KNeighborsClassifier</label><div class="sk-toggleable__content"><pre>KNeighborsClassifier(n_neighbors=3)</pre></div></div></div></div></div>
|
109 |
+
|
110 |
+
## Evaluation Results
|
111 |
+
|
112 |
+
[More Information Needed]
|
113 |
+
|
114 |
+
# How to Get Started with the Model
|
115 |
+
|
116 |
+
[More Information Needed]
|
117 |
+
|
118 |
+
# Model Card Authors
|
119 |
+
|
120 |
+
This model card is written by following authors:
|
121 |
+
|
122 |
+
[More Information Needed]
|
123 |
+
|
124 |
+
# Model Card Contact
|
125 |
+
|
126 |
+
You can contact the model card authors through following channels:
|
127 |
+
[More Information Needed]
|
128 |
+
|
129 |
+
# Citation
|
130 |
+
|
131 |
+
Below you can find information related to citation.
|
132 |
+
|
133 |
+
**BibTeX:**
|
134 |
+
```
|
135 |
+
[More Information Needed]
|
136 |
+
```
|
config.json
ADDED
@@ -0,0 +1,108 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"sklearn": {
|
3 |
+
"columns": [
|
4 |
+
"x0",
|
5 |
+
"x1",
|
6 |
+
"x2",
|
7 |
+
"x3",
|
8 |
+
"x4",
|
9 |
+
"x5",
|
10 |
+
"x6",
|
11 |
+
"x7",
|
12 |
+
"x8",
|
13 |
+
"x9",
|
14 |
+
"x10",
|
15 |
+
"x11",
|
16 |
+
"x12",
|
17 |
+
"x13",
|
18 |
+
"x14"
|
19 |
+
],
|
20 |
+
"environment": [
|
21 |
+
"scikit-learn=1.2.1",
|
22 |
+
"scikit-learn-intelex=2023.0.1"
|
23 |
+
],
|
24 |
+
"example_input": {
|
25 |
+
"x0": [
|
26 |
+
-2.91869894329896,
|
27 |
+
1.2861311367611363,
|
28 |
+
-0.17676780746347887
|
29 |
+
],
|
30 |
+
"x1": [
|
31 |
+
4.378017491251676,
|
32 |
+
-3.150744413325807,
|
33 |
+
-3.268596999474564
|
34 |
+
],
|
35 |
+
"x10": [
|
36 |
+
0.8047174523586147,
|
37 |
+
-1.2969581776011339,
|
38 |
+
0.31762144434782824
|
39 |
+
],
|
40 |
+
"x11": [
|
41 |
+
-3.2390344195350487,
|
42 |
+
1.1959946004673214,
|
43 |
+
0.7563114595834011
|
44 |
+
],
|
45 |
+
"x12": [
|
46 |
+
-0.5746008540164298,
|
47 |
+
3.3486745844798804,
|
48 |
+
2.948767259442758
|
49 |
+
],
|
50 |
+
"x13": [
|
51 |
+
3.5915430703361673,
|
52 |
+
3.5265729573580655,
|
53 |
+
0.015963649217312414
|
54 |
+
],
|
55 |
+
"x14": [
|
56 |
+
0.8137258237766396,
|
57 |
+
-3.6846723813183138,
|
58 |
+
-0.0726270826536789
|
59 |
+
],
|
60 |
+
"x2": [
|
61 |
+
1.660608706929798,
|
62 |
+
-2.915945269906298,
|
63 |
+
-0.2966018717870358
|
64 |
+
],
|
65 |
+
"x3": [
|
66 |
+
5.717843051082721,
|
67 |
+
0.6565179693281937,
|
68 |
+
3.2575477536637036
|
69 |
+
],
|
70 |
+
"x4": [
|
71 |
+
-1.319254071176227,
|
72 |
+
3.2948523559028287,
|
73 |
+
1.5435232801320602
|
74 |
+
],
|
75 |
+
"x5": [
|
76 |
+
-2.9780546324477646,
|
77 |
+
-1.3618488406102902,
|
78 |
+
1.5867699986090962
|
79 |
+
],
|
80 |
+
"x6": [
|
81 |
+
1.6471024314152358,
|
82 |
+
1.3658191827488237,
|
83 |
+
-1.4529064414158699
|
84 |
+
],
|
85 |
+
"x7": [
|
86 |
+
0.3525021389263907,
|
87 |
+
1.3302365122960365,
|
88 |
+
0.09438131139298833
|
89 |
+
],
|
90 |
+
"x8": [
|
91 |
+
-0.44858117376143913,
|
92 |
+
0.9049016837557153,
|
93 |
+
2.195212749960551
|
94 |
+
],
|
95 |
+
"x9": [
|
96 |
+
0.5394501179095126,
|
97 |
+
-2.85779169799503,
|
98 |
+
1.3981326527555564
|
99 |
+
]
|
100 |
+
},
|
101 |
+
"model": {
|
102 |
+
"file": "model-optimized.pkl"
|
103 |
+
},
|
104 |
+
"model_format": "pickle",
|
105 |
+
"task": "tabular-classification",
|
106 |
+
"use_intelex": true
|
107 |
+
}
|
108 |
+
}
|
model-optimized.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:29ed9b1bb74cd9c84c616bea51df1a28d3dc6a52b0416967d72fbd11ee2830b1
|
3 |
+
size 9652316
|