Add scikit-learn KNN model example
Browse files- README.md +135 -0
- config.json +107 -0
- model-stock.pkl +3 -0
README.md
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---
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library_name: sklearn
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tags:
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- sklearn
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- skops
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- tabular-classification
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model_format: pickle
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model_file: model-stock.pkl
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widget:
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structuredData:
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x0:
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- -2.91869894329896
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- 1.2861311367611363
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- -0.17676780746347887
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x1:
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- 4.378017491251676
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- -3.150744413325807
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- -3.268596999474564
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x10:
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- 0.8047174523586147
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- -1.2969581776011339
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- 0.31762144434782824
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x11:
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- -3.2390344195350487
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- 1.1959946004673214
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- 0.7563114595834011
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x12:
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- -0.5746008540164298
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- 3.3486745844798804
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- 2.948767259442758
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x13:
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- 3.5915430703361673
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- 3.5265729573580655
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- 0.015963649217312414
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x14:
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- 0.8137258237766396
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- -3.6846723813183138
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- -0.0726270826536789
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x2:
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- 1.660608706929798
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- -2.915945269906298
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- -0.2966018717870358
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x3:
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- 5.717843051082721
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- 0.6565179693281937
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- 3.2575477536637036
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x4:
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- -1.319254071176227
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- 3.2948523559028287
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- 1.5435232801320602
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x5:
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- -2.9780546324477646
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- -1.3618488406102902
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- 1.5867699986090962
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x6:
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- 1.6471024314152358
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- 1.3658191827488237
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- -1.4529064414158699
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x7:
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- 0.3525021389263907
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- 1.3302365122960365
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- 0.09438131139298833
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x8:
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- -0.44858117376143913
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- 0.9049016837557153
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- 2.195212749960551
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x9:
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- 0.5394501179095126
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- -2.85779169799503
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- 1.3981326527555564
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---
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# Model description
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[More Information Needed]
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## Intended uses & limitations
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[More Information Needed]
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## Training Procedure
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### Hyperparameters
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The model is trained with below hyperparameters.
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<details>
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<summary> Click to expand </summary>
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| Hyperparameter | Value |
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|------------------|-----------|
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| algorithm | auto |
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| leaf_size | 30 |
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| metric | minkowski |
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| metric_params | |
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| n_jobs | |
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| n_neighbors | 3 |
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| p | 2 |
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| weights | uniform |
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</details>
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### Model Plot
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The model plot is below.
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<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>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-1" type="checkbox" checked><label for="sk-estimator-id-1" 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>
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## Evaluation Results
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[More Information Needed]
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# How to Get Started with the Model
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[More Information Needed]
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# Model Card Authors
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This model card is written by following authors:
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[More Information Needed]
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# Model Card Contact
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You can contact the model card authors through following channels:
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[More Information Needed]
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# Citation
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Below you can find information related to citation.
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**BibTeX:**
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```
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[More Information Needed]
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```
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config.json
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{
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"sklearn": {
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"columns": [
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"x0",
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"x1",
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"x2",
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"x3",
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"x4",
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"x5",
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"x6",
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"x7",
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"x8",
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"x9",
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"x10",
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"x11",
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"x12",
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"x13",
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"x14"
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],
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"environment": [
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"scikit-learn=1.2.1"
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],
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"example_input": {
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"x0": [
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-2.91869894329896,
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1.2861311367611363,
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-0.17676780746347887
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],
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"x1": [
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4.378017491251676,
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-3.150744413325807,
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-3.268596999474564
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],
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"x10": [
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0.8047174523586147,
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-1.2969581776011339,
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+
0.31762144434782824
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],
|
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"x11": [
|
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+
-3.2390344195350487,
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+
1.1959946004673214,
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+
0.7563114595834011
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],
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"x12": [
|
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-0.5746008540164298,
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3.3486745844798804,
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2.948767259442758
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],
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"x13": [
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+
3.5915430703361673,
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+
3.5265729573580655,
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52 |
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0.015963649217312414
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],
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"x14": [
|
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0.8137258237766396,
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+
-3.6846723813183138,
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-0.0726270826536789
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],
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"x2": [
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1.660608706929798,
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+
-2.915945269906298,
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-0.2966018717870358
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],
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"x3": [
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5.717843051082721,
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0.6565179693281937,
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+
3.2575477536637036
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],
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"x4": [
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-1.319254071176227,
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3.2948523559028287,
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1.5435232801320602
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],
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"x5": [
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-2.9780546324477646,
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-1.3618488406102902,
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1.5867699986090962
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],
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"x6": [
|
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+
1.6471024314152358,
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+
1.3658191827488237,
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+
-1.4529064414158699
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],
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"x7": [
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0.3525021389263907,
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+
1.3302365122960365,
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+
0.09438131139298833
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],
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"x8": [
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-0.44858117376143913,
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+
0.9049016837557153,
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+
2.195212749960551
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],
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"x9": [
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+
0.5394501179095126,
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-2.85779169799503,
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+
1.3981326527555564
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]
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},
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"model": {
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"file": "model-stock.pkl"
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},
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"model_format": "pickle",
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"task": "tabular-classification",
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"use_intelex": false
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}
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}
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model-stock.pkl
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:37560d8d2e3570c2a6ca70bac98aefd9faf35335b78c574e6b2cda7072d6b8d3
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size 5317998
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