RF Feature Importance (based on Python Library)

This Component can be used to visualise the Feature/variable importance in a binary classification sceanrio. It used the Random forest importance calculater function in python to calculate the importance of the variables.

The python script nodes are encapsulated in this component, the user do not have to set up the python environment, the conda propagation node will set up all the required libararies to the user system

Can be used on KAP version 4.3 and above

Options

Select Target Column: Enter Description

Input Ports

: Input data with binary target

Output Ports

: Feature Importance table

Nodes

Table Row to Variable4 ×
Column Filter3 ×
Breakpoint2 ×
CASE Switch Data (Start)2 ×
Column Appender2 ×
Python Script (legacy)2 ×
Rule Engine Variable2 ×
Bar Chart1 ×
Column Rename1 ×
Column Selection Configuration1 ×
Column Splitter1 ×
Component Input1 ×
Component Output1 ×
Conda Environment Propagation1 ×
Extract Table Dimension1 ×
GroupBy1 ×
Merge Variables1 ×
Missing Value1 ×
Rule Engine1 ×
Sorter1 ×
Text Output Widget1 ×

Extensions

FeatureKNIME Base nodes
FeatureKNIME JavaScript Views
FeatureKNIME Javasnippet
FeatureKNIME Python 2 Integration (legacy)
FeatureKNIME Quick Forms