Binarize

Binarizes continuous features.

This operation is ported from Spark ML.

For a comprehensive introduction, see Spark documentation.

For scala docs details, see org.apache.spark.ml.feature.Binarizer documentation.

Since: Seahorse 1.0.0

Input

Port	Type Qualifier	Description
`0`	`DataFrame`	The input `DataFrame`.

Output

Port	Type Qualifier	Description
`0`	`DataFrame`	The output `DataFrame`.
`1`	`Transformer`	A `Transformer` that allows to apply the operation on other `DataFrames` using a Transform.

Parameters

Name	Type	Description
`threshold`	`Numeric`	The threshold used to binarize continuous features. Feature values greater than the threshold will be binarized to 1.0. Remaining values will be binarized to 0.0.
`operate on`	`InputOutputColumnSelector`	The input and output columns for the operation.

Example

Parameters

Name	Value
`threshold`	0.5
`operate on`	one column
`input column`	"hum"
`output`	append new column
`output column`	"hum_bin"

Input

datetime	windspeed	hum	temp
2011-01-03 21:00:00.0	0.1045	0.47	0.2
2011-01-03 22:00:00.0	0.1343	0.64	0.18
2011-01-03 23:00:00.0	0.1343	0.69	0.14
2011-02-11 07:00:00.0	0.0	0.68	0.1
2011-02-13 18:00:00.0	0.3284	0.28	0.42
2011-02-18 12:00:00.0	0.1642	0.72	0.44
2011-02-19 03:00:00.0	0.3881	0.13	0.44
2011-02-19 04:00:00.0	0.2985	0.14	0.42
2013-01-01 00:00:00.0	0.1343	0.65	0.26

Output

datetime	windspeed	hum	temp	hum_bin
2011-01-03 21:00:00.0	0.1045	0.47	0.2	0.0
2011-01-03 22:00:00.0	0.1343	0.64	0.18	1.0
2011-01-03 23:00:00.0	0.1343	0.69	0.14	1.0
2011-02-11 07:00:00.0	0.0	0.68	0.1	1.0
2011-02-13 18:00:00.0	0.3284	0.28	0.42	0.0
2011-02-18 12:00:00.0	0.1642	0.72	0.44	1.0
2011-02-19 03:00:00.0	0.3881	0.13	0.44	0.0
2011-02-19 04:00:00.0	0.2985	0.14	0.42	0.0
2013-01-01 00:00:00.0	0.1343	0.65	0.26	1.0