Sklearn Binarizer

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

Type

transform

Class

fire.nodes.sklearn.preprocessing.NodeBinarizerFitTransform

Fields

Name	Title	Description
threshold	Threshold

Details

Sklearn Binarizer Node Details

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

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

Sklearn Binarizer Node Example

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.