C4.5
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C4.5 Algorithm - A Decision Tree for Numerical and Categorical Data that can Handle Missing Values and Pruning Methods
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this column "0" is actually the `y` which was added by the train function at first to the `X` dataframe, but mistakenly goes into the decision parameters. with this mistake...
Hi, Not a big issue, but just wanted to share that you might need to reset the dataframe indices (of Xdata and ydata) before entering them into dt_c45(). The indices...
I mean the output of the script here is a list of IF-THEN rules cant we convert it to an image that contain the decision tree ?