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    Kik bots spamMar 08, 2020 · Examining Multicollinearity. Lastly, we checked for variables with high correlation with each other (multicollinearity). We did so because one of the required assumptions for linear regression models involving multiple variables is that there is little-to-no multicollinearity between feature variables.
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See full list on machinelearningmastery.com Mac mouse scroll wheel reverseJun 15, 2020 · The above two cases are where the target variable is a bivariate one i.e. with only two categories of response. There can be cases where the target variable has more than two categories, the decision tree can be applied in such multinomial cases too. The decision tree can also handle both numerical and categorical data. So, no doubt a decision ...

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