Binarizer

Binarize a column of continuous features given a threshold.

Input

This type of node takes in a DataFrame and transforms it to another DataFrame

Output

A new column containing the binarized values is added to the incoming DataFrame

Type

ml-transformer

Class

fire.nodes.ml.NodeBinarizer

Fields

Name	Title	Description
inputCol	Input Column	The input column name
outputCol	Output Column	The output column name
threshold	Threshold	The features greater than the threshold, will be binarized to 1.0.The features equal to or less than the threshold, will be binarized to 0.0.

Details

Binarizer Node Details

The Binarizer Node is used in the process of thresholding numerical features to binary (0/1) features.

Binarizer takes the common parameters inputCol and outputCol, as well as the threshold for binarization.

Feature values greater than the threshold are binarized to 1.0; values equal to or less than the threshold are binarized to 0.0.

Both Vector and Double types are supported for inputCol.

Input Parameters

• OUTPUT STORAGE LEVEL : Keep this as DEFAULT.

• INPUT COLUMN : Select the required column for whom binarization has to be done .

• OUTPUT COLUMN : The name of the output binarized column.

• THRESHOLD : Set the threshold used to binarize continuous features. The features greater than the threshold, will be binarized to 1.0. The features equal to or less than the threshold, will be binarized to 0.0. Default: 0.0

Examples

Binarization Node Example

Consider the below Binarizer output for the feature column with Threshold set to 0.5

-------------------------------
| id|feature|binarized_feature|
-------------------------------
|  0|    0.1|              0.0|
|  1|    0.8|              1.0|
|  2|    0.2|              0.0|
-------------------------------