noteJ

noteJ

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Numeric underflow stratified sampling Nearest Neighbor Classifier Apriori algorithm MLP calculation association rules Automated Test Naïve Bayes classifier multiple classification data-mining Dimensionality Reduction Pre-processing variable transformation zero count Curse of dimensionality feature subset selection pre processing LVQ discretization feature creation

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stratified sampling(1)

  • Advantages of stratified sampling over standard random sampling.

    Stratified sampling is a sampling technique that involves dividing a population into smaller subgroups or strata and then randomly sampling from each subgroup to ensure that the sample is representative of the overall population. This approach has several advantages over standard random sampling, which involves selecting individuals or elements from the population at random without regard to any..

    2023.03.05
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