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add json to manifest
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MANIFEST.in

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@@ -4,6 +4,8 @@ include HISTORY.md
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include LICENSE
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include README.md
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recursive-include zephyr_ml *.json
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recursive-include tests *
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recursive-exclude * __pycache__
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recursive-exclude * *.py[co]

README.md

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@@ -214,9 +214,6 @@ Once we have the feature matrix, we can train a model using the Zephyr interface
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First, we need to prepare our dataset for training such as imputed missing values.
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```python3
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from sklearn.impute import SimpleImputer
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# pop the target labels
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y = list(feature_matrix.pop('label'))
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X = pd.get_dummies(feature_matrix).values
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```
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```python3
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from zephyr_ml import Zephyr
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zephyr = Zephyr('xgb_regressor')
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pipeline_name = 'xgb_regressor'
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zephyr = Zephyr(pipeline_name)
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```
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To train the pipeline, we simply use the `fit` function.
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```
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After it finished training, we can make prediciton using `predict`
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```python3
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y_pred = zephyr.predict(X)
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```

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