pushing files to the repo from the example!
Browse files- README.md +73 -71
- config.json +68 -68
- confusion_matrix.png +0 -0
- model.pkl +1 -1
- tree.png +0 -0
README.md
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attribute_1:
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---
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# Model description
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The model plot is below.
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<style>#sk-cbcf73f3-3df0-460c-a28c-e975797de98c {color: black;background-color: white;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c pre{padding: 0;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-toggleable {background-color: white;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c 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-cbcf73f3-3df0-460c-a28c-e975797de98c 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-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-estimator:hover {background-color: #d4ebff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-item {z-index: 1;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item:only-child::after {width: 0;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c 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;position: relative;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-label-container {position: relative;z-index: 2;text-align: center;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c 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-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-text-repr-fallback {display: none;}</style><div id="sk-cbcf73f3-3df0-460c-a28c-e975797de98c" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[('transformation',ColumnTransformer(transformers=[('loading_missing_value_imputer',SimpleImputer(),['loading']),('numerical_missing_value_imputer',SimpleImputer(),['loading', 'measurement_3','measurement_4','measurement_5','measurement_6','measurement_7','measurement_8','measurement_9','measurement_10','measurement_11','measurement_12','measurement_13','measurement_14','measurement_15','measurement_16','measurement_17']),('attribute_0_encoder',OneHotEncoder(),['attribute_0']),('attribute_1_encoder',OneHotEncoder(),['attribute_1']),('product_code_encoder',OneHotEncoder(),['product_code'])])),('model', DecisionTreeClassifier(max_depth=4))])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</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="4039f6df-38bb-4617-ac8b-f6e94de8a91c" type="checkbox" ><label for="4039f6df-38bb-4617-ac8b-f6e94de8a91c" class="sk-toggleable__label sk-toggleable__label-arrow">Pipeline</label><div class="sk-toggleable__content"><pre>Pipeline(steps=[('transformation',ColumnTransformer(transformers=[('loading_missing_value_imputer',SimpleImputer(),['loading']),('numerical_missing_value_imputer',SimpleImputer(),['loading', 'measurement_3','measurement_4','measurement_5','measurement_6','measurement_7','measurement_8','measurement_9','measurement_10','measurement_11','measurement_12','measurement_13','measurement_14','measurement_15','measurement_16','measurement_17']),('attribute_0_encoder',OneHotEncoder(),['attribute_0']),('attribute_1_encoder',OneHotEncoder(),['attribute_1']),('product_code_encoder',OneHotEncoder(),['product_code'])])),('model', DecisionTreeClassifier(max_depth=4))])</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="61e07386-e7b7-418a-9af8-41b0261577b4" type="checkbox" ><label for="61e07386-e7b7-418a-9af8-41b0261577b4" class="sk-toggleable__label sk-toggleable__label-arrow">transformation: ColumnTransformer</label><div class="sk-toggleable__content"><pre>ColumnTransformer(transformers=[('loading_missing_value_imputer',SimpleImputer(), ['loading']),('numerical_missing_value_imputer',SimpleImputer(),['loading', 'measurement_3', 'measurement_4','measurement_5', 'measurement_6','measurement_7', 'measurement_8','measurement_9', 'measurement_10','measurement_11', 'measurement_12','measurement_13', 'measurement_14','measurement_15', 'measurement_16','measurement_17']),('attribute_0_encoder', OneHotEncoder(),['attribute_0']),('attribute_1_encoder', OneHotEncoder(),['attribute_1']),('product_code_encoder', OneHotEncoder(),['product_code'])])</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="543953aa-7345-4433-b640-9ebcb9cfaed6" type="checkbox" ><label for="543953aa-7345-4433-b640-9ebcb9cfaed6" class="sk-toggleable__label sk-toggleable__label-arrow">loading_missing_value_imputer</label><div class="sk-toggleable__content"><pre>['loading']</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="28f1b85a-54e9-44db-b914-819af4998fd1" type="checkbox" ><label for="28f1b85a-54e9-44db-b914-819af4998fd1" class="sk-toggleable__label sk-toggleable__label-arrow">SimpleImputer</label><div class="sk-toggleable__content"><pre>SimpleImputer()</pre></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="d8710d93-e747-4796-95d5-77538856cb1d" type="checkbox" ><label for="d8710d93-e747-4796-95d5-77538856cb1d" class="sk-toggleable__label sk-toggleable__label-arrow">numerical_missing_value_imputer</label><div class="sk-toggleable__content"><pre>['loading', 'measurement_3', 'measurement_4', 'measurement_5', 'measurement_6', 'measurement_7', 'measurement_8', 'measurement_9', 'measurement_10', 'measurement_11', 'measurement_12', 'measurement_13', 'measurement_14', 'measurement_15', 'measurement_16', 'measurement_17']</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="b23ea887-b3eb-4dbc-ba26-dd3e0e018c70" type="checkbox" ><label for="b23ea887-b3eb-4dbc-ba26-dd3e0e018c70" class="sk-toggleable__label sk-toggleable__label-arrow">SimpleImputer</label><div class="sk-toggleable__content"><pre>SimpleImputer()</pre></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="c87a37af-e576-4840-bf8c-7e7f5b8ab39e" type="checkbox" ><label for="c87a37af-e576-4840-bf8c-7e7f5b8ab39e" class="sk-toggleable__label sk-toggleable__label-arrow">attribute_0_encoder</label><div class="sk-toggleable__content"><pre>['attribute_0']</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="580ea11e-4df6-4bce-b994-dc4d342d42d4" type="checkbox" ><label for="580ea11e-4df6-4bce-b994-dc4d342d42d4" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder()</pre></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="8ccfa95c-d0f7-4dd2-8be2-0885a564d231" type="checkbox" ><label for="8ccfa95c-d0f7-4dd2-8be2-0885a564d231" class="sk-toggleable__label sk-toggleable__label-arrow">attribute_1_encoder</label><div class="sk-toggleable__content"><pre>['attribute_1']</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="e1ed00d2-3cb6-43cd-9ba5-bc0518c93345" type="checkbox" ><label for="e1ed00d2-3cb6-43cd-9ba5-bc0518c93345" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder()</pre></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="b94ddf76-0075-4efc-9cc4-8c6b69fefad5" type="checkbox" ><label for="b94ddf76-0075-4efc-9cc4-8c6b69fefad5" class="sk-toggleable__label sk-toggleable__label-arrow">product_code_encoder</label><div class="sk-toggleable__content"><pre>['product_code']</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="1d06bc4d-04b9-44d6-a23f-cdc26d70b7e2" type="checkbox" ><label for="1d06bc4d-04b9-44d6-a23f-cdc26d70b7e2" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder()</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="208c2a51-a582-469b-9bd1-23b9a3968840" type="checkbox" ><label for="208c2a51-a582-469b-9bd1-23b9a3968840" class="sk-toggleable__label sk-toggleable__label-arrow">DecisionTreeClassifier</label><div class="sk-toggleable__content"><pre>DecisionTreeClassifier(max_depth=4)</pre></div></div></div></div></div></div></div>
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## Evaluation Results
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| Metric | Value |
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# How to Get Started with the Model
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```
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Confusion Matrix
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attribute_1:
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attribute_3:
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loading:
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- 101.52
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- 91.34
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measurement_0:
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- 9
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- 10
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measurement_1:
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- 11
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- 5
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measurement_10:
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- 14.926
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- 15.162
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- 16.398
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measurement_11:
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- 20.394
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- 19.46
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- 20.613
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measurement_12:
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- 11.829
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- 9.114
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- 11.007
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measurement_13:
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- 16.195
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- 16.024
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- 16.061
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measurement_14:
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- 16.517
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- 17.132
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- 15.18
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measurement_15:
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- 13.826
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- 12.257
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- 15.758
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measurement_16:
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- 14.206
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- 15.094
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- .nan
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measurement_17:
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- 723.712
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- 896.835
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- 893.454
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measurement_2:
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- 2
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- 10
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- 6
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measurement_3:
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- 17.492
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- 18.114
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- 18.42
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measurement_4:
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| 78 |
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- 13.962
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| 79 |
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- 10.185
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- 13.565
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measurement_5:
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- 15.716
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- 18.06
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- 16.916
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measurement_6:
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| 86 |
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- 17.104
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| 87 |
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- 18.283
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- 17.917
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measurement_7:
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| 90 |
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- 12.377
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- 10.957
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- 10.394
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measurement_8:
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| 94 |
+
- 19.221
|
| 95 |
+
- 20.638
|
| 96 |
+
- 19.805
|
| 97 |
measurement_9:
|
| 98 |
+
- 11.613
|
| 99 |
+
- 11.804
|
| 100 |
+
- 12.012
|
| 101 |
product_code:
|
| 102 |
+
- E
|
|
|
|
| 103 |
- D
|
| 104 |
+
- E
|
| 105 |
---
|
| 106 |
|
| 107 |
# Model description
|
|
|
|
| 220 |
|
| 221 |
The model plot is below.
|
| 222 |
|
| 223 |
+
<style>#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 {color: black;background-color: white;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 pre{padding: 0;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-toggleable {background-color: white;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 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-b5518c10-fd7e-49af-b124-60d3dd3d0f86 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-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-estimator:hover {background-color: #d4ebff;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-item {z-index: 1;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-parallel::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-parallel-item:only-child::after {width: 0;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 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;position: relative;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-label-container {position: relative;z-index: 2;text-align: center;}#sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86 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-b5518c10-fd7e-49af-b124-60d3dd3d0f86 div.sk-text-repr-fallback {display: none;}</style><div id="sk-b5518c10-fd7e-49af-b124-60d3dd3d0f86" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[('transformation',ColumnTransformer(transformers=[('loading_missing_value_imputer',SimpleImputer(),['loading']),('numerical_missing_value_imputer',SimpleImputer(),['loading', 'measurement_3','measurement_4','measurement_5','measurement_6','measurement_7','measurement_8','measurement_9','measurement_10','measurement_11','measurement_12','measurement_13','measurement_14','measurement_15','measurement_16','measurement_17']),('attribute_0_encoder',OneHotEncoder(),['attribute_0']),('attribute_1_encoder',OneHotEncoder(),['attribute_1']),('product_code_encoder',OneHotEncoder(),['product_code'])])),('model', DecisionTreeClassifier(max_depth=4))])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</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="48fbfeb0-e954-46f7-9a36-8dfe86284fca" type="checkbox" ><label for="48fbfeb0-e954-46f7-9a36-8dfe86284fca" class="sk-toggleable__label sk-toggleable__label-arrow">Pipeline</label><div class="sk-toggleable__content"><pre>Pipeline(steps=[('transformation',ColumnTransformer(transformers=[('loading_missing_value_imputer',SimpleImputer(),['loading']),('numerical_missing_value_imputer',SimpleImputer(),['loading', 'measurement_3','measurement_4','measurement_5','measurement_6','measurement_7','measurement_8','measurement_9','measurement_10','measurement_11','measurement_12','measurement_13','measurement_14','measurement_15','measurement_16','measurement_17']),('attribute_0_encoder',OneHotEncoder(),['attribute_0']),('attribute_1_encoder',OneHotEncoder(),['attribute_1']),('product_code_encoder',OneHotEncoder(),['product_code'])])),('model', DecisionTreeClassifier(max_depth=4))])</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="157828b7-30d1-4b5b-b25e-971143379fff" type="checkbox" ><label for="157828b7-30d1-4b5b-b25e-971143379fff" class="sk-toggleable__label sk-toggleable__label-arrow">transformation: ColumnTransformer</label><div class="sk-toggleable__content"><pre>ColumnTransformer(transformers=[('loading_missing_value_imputer',SimpleImputer(), ['loading']),('numerical_missing_value_imputer',SimpleImputer(),['loading', 'measurement_3', 'measurement_4','measurement_5', 'measurement_6','measurement_7', 'measurement_8','measurement_9', 'measurement_10','measurement_11', 'measurement_12','measurement_13', 'measurement_14','measurement_15', 'measurement_16','measurement_17']),('attribute_0_encoder', OneHotEncoder(),['attribute_0']),('attribute_1_encoder', OneHotEncoder(),['attribute_1']),('product_code_encoder', OneHotEncoder(),['product_code'])])</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="3bde7e44-3687-4b99-a3b7-b4e87023ec85" type="checkbox" ><label for="3bde7e44-3687-4b99-a3b7-b4e87023ec85" class="sk-toggleable__label sk-toggleable__label-arrow">loading_missing_value_imputer</label><div class="sk-toggleable__content"><pre>['loading']</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="ef9279cb-7d77-4ef1-aafe-26e433e2a615" type="checkbox" ><label for="ef9279cb-7d77-4ef1-aafe-26e433e2a615" class="sk-toggleable__label sk-toggleable__label-arrow">SimpleImputer</label><div class="sk-toggleable__content"><pre>SimpleImputer()</pre></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="b079e8d7-f789-4622-ad66-197193ef0061" type="checkbox" ><label for="b079e8d7-f789-4622-ad66-197193ef0061" class="sk-toggleable__label sk-toggleable__label-arrow">numerical_missing_value_imputer</label><div class="sk-toggleable__content"><pre>['loading', 'measurement_3', 'measurement_4', 'measurement_5', 'measurement_6', 'measurement_7', 'measurement_8', 'measurement_9', 'measurement_10', 'measurement_11', 'measurement_12', 'measurement_13', 'measurement_14', 'measurement_15', 'measurement_16', 'measurement_17']</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="969f6026-8077-468a-b332-8ceb69bac4e9" type="checkbox" ><label for="969f6026-8077-468a-b332-8ceb69bac4e9" class="sk-toggleable__label sk-toggleable__label-arrow">SimpleImputer</label><div class="sk-toggleable__content"><pre>SimpleImputer()</pre></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="5bb6cc8f-c971-47b8-a1bc-fe8053602d5c" type="checkbox" ><label for="5bb6cc8f-c971-47b8-a1bc-fe8053602d5c" class="sk-toggleable__label sk-toggleable__label-arrow">attribute_0_encoder</label><div class="sk-toggleable__content"><pre>['attribute_0']</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="8a841657-38e1-41bb-b8f9-5ad2cc25f7d3" type="checkbox" ><label for="8a841657-38e1-41bb-b8f9-5ad2cc25f7d3" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder()</pre></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="be08add7-98fc-40b5-a259-d462d738780a" type="checkbox" ><label for="be08add7-98fc-40b5-a259-d462d738780a" class="sk-toggleable__label sk-toggleable__label-arrow">attribute_1_encoder</label><div class="sk-toggleable__content"><pre>['attribute_1']</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="cf07a6c2-b92e-40b1-9862-2c1ca3baab47" type="checkbox" ><label for="cf07a6c2-b92e-40b1-9862-2c1ca3baab47" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder()</pre></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="244735dc-f1e1-458c-a1c6-60ef847b9cae" type="checkbox" ><label for="244735dc-f1e1-458c-a1c6-60ef847b9cae" class="sk-toggleable__label sk-toggleable__label-arrow">product_code_encoder</label><div class="sk-toggleable__content"><pre>['product_code']</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="2f1a1c41-e1c4-40ce-afd9-9658030b3423" type="checkbox" ><label for="2f1a1c41-e1c4-40ce-afd9-9658030b3423" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder()</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="25044b48-b814-45f9-a75b-9ee472bdc79c" type="checkbox" ><label for="25044b48-b814-45f9-a75b-9ee472bdc79c" class="sk-toggleable__label sk-toggleable__label-arrow">DecisionTreeClassifier</label><div class="sk-toggleable__content"><pre>DecisionTreeClassifier(max_depth=4)</pre></div></div></div></div></div></div></div>
|
| 224 |
|
| 225 |
## Evaluation Results
|
| 226 |
|
|
|
|
| 230 |
|
| 231 |
| Metric | Value |
|
| 232 |
|----------|----------|
|
| 233 |
+
| accuracy | 0.791961 |
|
| 234 |
+
| f1 score | 0.791961 |
|
| 235 |
|
| 236 |
# How to Get Started with the Model
|
| 237 |
|
|
|
|
| 272 |
```
|
| 273 |
|
| 274 |
|
| 275 |
+
# Additional Content
|
| 276 |
+
|
| 277 |
+
## Tree Plot
|
| 278 |
|
| 279 |
+
|
| 280 |
|
| 281 |
+
## Confusion Matrix
|
| 282 |
|
| 283 |
+
|
|
|
config.json
CHANGED
|
@@ -36,119 +36,119 @@
|
|
| 36 |
"material_7"
|
| 37 |
],
|
| 38 |
"attribute_1": [
|
| 39 |
-
"
|
| 40 |
-
"
|
| 41 |
-
"
|
| 42 |
],
|
| 43 |
"attribute_2": [
|
| 44 |
-
|
| 45 |
-
|
| 46 |
6
|
| 47 |
],
|
| 48 |
"attribute_3": [
|
| 49 |
-
|
| 50 |
-
|
| 51 |
-
|
| 52 |
],
|
| 53 |
"loading": [
|
| 54 |
-
|
| 55 |
-
|
| 56 |
-
|
| 57 |
],
|
| 58 |
"measurement_0": [
|
| 59 |
-
|
| 60 |
-
|
| 61 |
-
|
| 62 |
],
|
| 63 |
"measurement_1": [
|
| 64 |
-
|
| 65 |
-
|
| 66 |
-
|
| 67 |
],
|
| 68 |
"measurement_10": [
|
| 69 |
-
|
| 70 |
-
15.
|
| 71 |
-
|
| 72 |
],
|
| 73 |
"measurement_11": [
|
| 74 |
-
|
| 75 |
-
|
| 76 |
-
20.
|
| 77 |
],
|
| 78 |
"measurement_12": [
|
| 79 |
-
|
| 80 |
-
|
| 81 |
-
|
| 82 |
],
|
| 83 |
"measurement_13": [
|
| 84 |
-
|
| 85 |
-
|
| 86 |
-
|
| 87 |
],
|
| 88 |
"measurement_14": [
|
| 89 |
-
|
| 90 |
-
|
| 91 |
-
|
| 92 |
],
|
| 93 |
"measurement_15": [
|
| 94 |
-
|
| 95 |
-
|
| 96 |
-
|
| 97 |
],
|
| 98 |
"measurement_16": [
|
| 99 |
-
|
| 100 |
-
|
| 101 |
-
|
| 102 |
],
|
| 103 |
"measurement_17": [
|
| 104 |
-
|
| 105 |
-
|
| 106 |
-
|
| 107 |
],
|
| 108 |
"measurement_2": [
|
| 109 |
-
|
| 110 |
-
|
| 111 |
-
|
| 112 |
],
|
| 113 |
"measurement_3": [
|
| 114 |
-
|
| 115 |
-
18.
|
| 116 |
-
|
| 117 |
],
|
| 118 |
"measurement_4": [
|
| 119 |
-
|
| 120 |
-
10.
|
| 121 |
-
|
| 122 |
],
|
| 123 |
"measurement_5": [
|
| 124 |
-
|
| 125 |
-
|
| 126 |
-
|
| 127 |
],
|
| 128 |
"measurement_6": [
|
| 129 |
-
|
| 130 |
-
|
| 131 |
-
17.
|
| 132 |
],
|
| 133 |
"measurement_7": [
|
| 134 |
-
|
| 135 |
-
|
| 136 |
-
|
| 137 |
],
|
| 138 |
"measurement_8": [
|
| 139 |
-
|
| 140 |
-
|
| 141 |
-
|
| 142 |
],
|
| 143 |
"measurement_9": [
|
| 144 |
-
|
| 145 |
-
|
| 146 |
-
|
| 147 |
],
|
| 148 |
"product_code": [
|
| 149 |
-
"
|
| 150 |
-
"
|
| 151 |
-
"
|
| 152 |
]
|
| 153 |
},
|
| 154 |
"model": {
|
|
|
|
| 36 |
"material_7"
|
| 37 |
],
|
| 38 |
"attribute_1": [
|
| 39 |
+
"material_6",
|
| 40 |
+
"material_5",
|
| 41 |
+
"material_6"
|
| 42 |
],
|
| 43 |
"attribute_2": [
|
| 44 |
+
6,
|
| 45 |
+
6,
|
| 46 |
6
|
| 47 |
],
|
| 48 |
"attribute_3": [
|
| 49 |
+
9,
|
| 50 |
+
6,
|
| 51 |
+
9
|
| 52 |
],
|
| 53 |
"loading": [
|
| 54 |
+
101.52,
|
| 55 |
+
91.34,
|
| 56 |
+
167.03
|
| 57 |
],
|
| 58 |
"measurement_0": [
|
| 59 |
+
9,
|
| 60 |
+
10,
|
| 61 |
+
11
|
| 62 |
],
|
| 63 |
"measurement_1": [
|
| 64 |
+
11,
|
| 65 |
+
11,
|
| 66 |
+
5
|
| 67 |
],
|
| 68 |
"measurement_10": [
|
| 69 |
+
14.926,
|
| 70 |
+
15.162,
|
| 71 |
+
16.398
|
| 72 |
],
|
| 73 |
"measurement_11": [
|
| 74 |
+
20.394,
|
| 75 |
+
19.46,
|
| 76 |
+
20.613
|
| 77 |
],
|
| 78 |
"measurement_12": [
|
| 79 |
+
11.829,
|
| 80 |
+
9.114,
|
| 81 |
+
11.007
|
| 82 |
],
|
| 83 |
"measurement_13": [
|
| 84 |
+
16.195,
|
| 85 |
+
16.024,
|
| 86 |
+
16.061
|
| 87 |
],
|
| 88 |
"measurement_14": [
|
| 89 |
+
16.517,
|
| 90 |
+
17.132,
|
| 91 |
+
15.18
|
| 92 |
],
|
| 93 |
"measurement_15": [
|
| 94 |
+
13.826,
|
| 95 |
+
12.257,
|
| 96 |
+
15.758
|
| 97 |
],
|
| 98 |
"measurement_16": [
|
| 99 |
+
14.206,
|
| 100 |
+
15.094,
|
| 101 |
+
NaN
|
| 102 |
],
|
| 103 |
"measurement_17": [
|
| 104 |
+
723.712,
|
| 105 |
+
896.835,
|
| 106 |
+
893.454
|
| 107 |
],
|
| 108 |
"measurement_2": [
|
| 109 |
+
2,
|
| 110 |
+
10,
|
| 111 |
+
6
|
| 112 |
],
|
| 113 |
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|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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|
| 118 |
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|
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|
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|
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| 124 |
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|
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|
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|
| 127 |
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|
| 128 |
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|
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|
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|
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|
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|
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"model": {
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confusion_matrix.png
CHANGED
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model.pkl
CHANGED
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