Sklearn Binarizer
===========

Binarize data (set feature values to 0 or 1) according to a threshold.

Type
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transform

Class
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fire.nodes.sklearn.preprocessing.NodeBinarizerFitTransform

Fields
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.. list-table::
      :widths: 10 5 10
      :header-rows: 1

      * - Name
        - Title
        - Description
      * - threshold
        - Threshold
        - 


Details
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Sklearn Binarizer Node Details
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The Sklearn Binarizer Node is used to binarize data, meaning it sets feature values to 0 or 1 according to a threshold. The threshold parameter is the value above which the features will be set to 1 and below which the features will be set to 0. It is a scalar value.


It takes in the input data and applies the threshold to the feature values. The input data can be in the form of a numpy array or a pandas DataFrame.



Input Parameters
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THRESHOLD : A scalar value above which the feature values will be set to 1 and below which the feature values will be set to 0.


Examples
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Sklearn Binarizer Node Example
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Consider the below **Sklearn Binarizer** output for the **features** column


id features binarized_features

0 [1.0, 2.0, 3.0, 4.0] [0, 0, 0, 1]

1 [-1.0, -2.0, -3.0, -4.0] [0, 0, 0, 0]

In this example, the input column is features and the output column is binarized_features. The threshold is set to 0.0. The feature values above threshold are set to 1 and below threshold are set to 0. In this example all feature values are greater than 0.0 so the binarized_features column will have all 1's.