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There is an error in the entropy calculation so the tree generated is wrong by the ID3 code.
I modify the loop at row 38 of DecisionTree.py in this way
i = 0
for entry in attributes:
if (targetAttr != entry):
i+=1
else:
break
if you modify that there is another bug on the ChooseAttrib function, it will select the highest gain value attrib, that is the target, just remove the target from the list of the attributes.
Nice code
The text was updated successfully, but these errors were encountered:
There is an error in the entropy calculation so the tree generated is wrong by the ID3 code.
I modify the loop at row 38 of DecisionTree.py in this way
i = 0
for entry in attributes:
if (targetAttr != entry):
i+=1
else:
break
if you modify that there is another bug on the ChooseAttrib function, it will select the highest gain value attrib, that is the target, just remove the target from the list of the attributes.
Nice code
The text was updated successfully, but these errors were encountered: