Given a dataset with 100 attributes, is it true that the classification performance is more accurate on the testing data
Posted: Mon Jun 06, 2022 5:17 pm
Given a dataset with 100 attributes, is it true that the
classification performance is more accurate on the testing dataset
if we use more attributes to split the dataset and why?
Please propose two methods to restrict the decision tree models in
order to avoid overfitting.
classification performance is more accurate on the testing dataset
if we use more attributes to split the dataset and why?
Please propose two methods to restrict the decision tree models in
order to avoid overfitting.