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Efficient huge-scale feature selection with speciated genetic algorithm

Efficient huge-scale feature selection with speciated genetic algorithm. Pattern Recognition Letters 27 (2006) 143–150. Jin-Hyuk Hong, Sung-Bae Cho Yonsei University, Korea. Standard Genetic Algorithm. - # chromosomes fitness  P(reproduction) Crossover Mutation. Proposed method SGANN.

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Efficient huge-scale feature selection with speciated genetic algorithm

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  1. Efficient huge-scale feature selection with speciated genetic algorithm Pattern Recognition Letters 27 (2006) 143–150 Jin-Hyuk Hong, Sung-Bae Cho Yonsei University, Korea Coffee Talk

  2. Standard Genetic Algorithm • - # chromosomes • fitness  P(reproduction) • Crossover • Mutation Coffee Talk

  3. Proposed method SGANN Coffee Talk

  4. Speciation by fitness sharing 0 <= similarity <= 1 mi : neighborhood density Coffee Talk

  5. Split chromosome for huge-scale feature selection The chromosome has just 25 genes (indices instead of 01) Coffee Talk

  6. 72x7219 Coffee Talk

  7. Coffee Talk

  8. Coffee Talk

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