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04_​Data_​Preprocessing_​for_​ML_​Models

Data Preprocessing for ML Models
This workflow demonstrates the standard preprocessing steps before training a machine learning model. Partition randomly80% for training20% for testHousingPrices Partitioning CSV Reader Outlier Detection Missing ValuesHandling Normalization DimensionalityReduction Conversion Feature Selection This workflow demonstrates the standard preprocessing steps before training a machine learning model. Partition randomly80% for training20% for testHousingPrices Partitioning CSV Reader Outlier Detection Missing ValuesHandling Normalization DimensionalityReduction Conversion Feature Selection

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: Lada.Rudnitckaia
Created at: 2021-08-18
On NodePit since: 2021-11-15
Last update: 2024-09-06
Created with KNIME version: v4.4.2
Tags: preprocessingpartitioningoutlier detectionmissing valuePCAencodingconversionforward feature selectionmachine learningML

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