Feature Selection
Feature selection is the process of choosing a subset of the most relevant input variables from a dataset to use in building a machine learning model, discarding redundant or uninformative features.
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Glossary Terms(3)
Feature Selection
Feature selection is the process of choosing a subset of the most relevant input variables from a dataset to use in building a machine learning model, discardi…
Dimensionality Reduction
Dimensionality reduction is the process of transforming data with many input variables into a lower-dimensional representation that preserves as much meaningfu…
Principal Component Analysis
Principal Component Analysis (PCA) is a linear dimensionality reduction technique that transforms correlated variables into a smaller set of uncorrelated compo…