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All Blog Posts Tagged 'random forests' (1)

Improving performance of random forests for a particular value of outcome by adding chosen features

Choosing features to improve a performance of a particular algorithm is a difficult question. Currently here is PCA, which is difficult to understand (although it can be used out-of-the-box), requires centralizing and scaling of features and is not easy to interpret. In addition, it does not allows to improve prediction performance for a particular outcome (if its accuracy is lower than for others or it has a particular importance). My method  enables to use features without preprocessing.…

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Added by Maiia Bakhova on May 5, 2016 at 11:30am — No Comments

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