Dm Encoding Categorical — Free Data Mining Tutorial
Learn Dm Encoding Categorical in Data Mining with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
TL;DR: Learn Dm Encoding Categorical in Data Mining with a free, beginner-friendly tutorial, examples and practice for Indian students on Syllab.in.
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Dm Encoding Categorical in Data Mining
Categorical variables contain discrete, non-numeric values (like city names, product categories). Machine learning algorithms require numerical input, so categorical data must be encoded.
One-Hot Encoding creates binary columns for each category (good for low cardinality). Label Encoding assigns numeric labels (good for ordinal data). Target Encoding uses target statistics.
Choosing the right encoding method affects model performance. Ordinal data preserves order with Label Encoding, while nominal data needs One-Hot Encoding to avoid imposing artificial ordering.
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