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03a. DimensionalityReduction - solution

Dimensionality reduction
Reduce the dimensionality based on the variance filter. Try different treshold. Hint: The higher the value, the more columns are likely to get filtered out. Check the lower dimensional data with statistics. Replace missing values by median (numerical) and by the most frequent value (nominal) Upper bound 0,9Missing valuetechniques for remaining columnsNumber of missingvalues after variance filterCheck the dimensionalityafter variance filterTitanicdataset Low Variance Filter Missing Value Statistics Extract TableDimension File Reader Reduce the dimensionality based on the variance filter. Try different treshold. Hint: The higher the value, the more columns are likely to get filtered out. Check the lower dimensional data with statistics. Replace missing values by median (numerical) and by the most frequent value (nominal) Upper bound 0,9Missing valuetechniques for remaining columnsNumber of missingvalues after variance filterCheck the dimensionalityafter variance filterTitanicdatasetLow Variance Filter Missing Value Statistics Extract TableDimension File Reader

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Created by: wiswedel
Created at: 2017-07-04
On NodePit since: 2020-12-05
Last update: 2024-04-27
Created with KNIME version: v4.2.3
Tags: high dimensionsdimensionality reductionmachine learningvisualization

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