Linear Discriminant analysis.pptx - Linear Discriminant analysis Introduction \u2022 goal of differentiating or discriminating the response variable into

Linear Discriminant analysis.pptx - Linear Discriminant...

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Linear Discriminant analysis
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Introduction goal of differentiating or discriminating the response variable into its distinct classes. most commonly used dimensionality reduction technique in supervised learning. preprocessing step for pattern classification and machine learning applications . minimize over fitting and computational costs. Under Linear Discriminant Analysis, we are basically looking for 1. Which set of parameters can best describe the association of the group for an object? 2. What is the best classification preceptor model that separates those groups?
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Linear Discriminant analysis Discriminant analysis is put to use when we already have predefined classes/categories of response and we want to build a model that helps in distinctly predicting the class , if any new observation comes into equation.
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Difference between LDA and PCA
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Difference between LDA and PCA LDA approach is very similar to Principal Component Analysis
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