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  3. Analyzing IoT Data in Python
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Store Pipeline

You'll now create the Pipeline again, but directly, skipping the step of initializing the StandardScaler and LogisticRegression as a variable. Instead, you will do the initialization as part of the Pipeline creation.

You'll then store the model for further use.

The data is available as X_train, with the labels as y_train.

StandardScaler, LogisticRegression and Pipeline have been imported for you.

说明 1 / 共 3 个

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  • Create a Pipeline object, using a StandardScaler and a LogisticRegression.
  • Fit the pipeline to X_train and y_train.