I\'m working on a program that takes in several (<50) high dimension points in feature space (1000+ dimensions) and performing hierarchical clustering on them by recursively using standard k-cluste
I want to use Random forests for attribute reduction. One problem I have in my data is that I don\'t have discrete class - only continuous, which indicates 开发者_运维知识库how example differs from \'
Consider having a dataset with Categorical-nominal feature types and one numerical output variable. Feature selection algorithms like InfoGain, Pearson or wrapper ones only accept numerical features a
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