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- W1519370596 abstract "A mechanism has been proposed to achieve optimal complexity for Discriminant Analysis (DA) based on Principal Component Analysis (PCA). We use PCA to filter non-informative features before applying to DA algorithm. In addition to significant accuracy improvement, the mechanism decreases the computational and storage costs of Linear Discriminant Analysis methods and makes the overall method more efficient. The mechanism helps classical linear DA methods outperform the state of the art and most superior linear and non-linear DA methods. Streszczenie. Zaproponowano mechanizm analizy zlozoności w analizie dyskryminacyjnej bazującej na Analizie Skladowej Glownej PCA. Dodatkowo mechanizm umozliwia poprawe dokladności klasyfikacji danych. (Analiza optymalnej zlozoności w analizie dyskryminacyjnej)" @default.
- W1519370596 created "2016-06-24" @default.
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- W1519370596 date "2011-01-01" @default.
- W1519370596 modified "2023-09-22" @default.
- W1519370596 title "Optimal complexity for discriminant analysis" @default.
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