Choose a disadvantage of decision trees among the following.Decision trees are robust to outliersFactor analysisDecision trees are prone to overfitAll of these

Choose a disadvantage of decision trees among the following.

Which of the following is a disadvantage of decision trees?Review LaterThey are computationally expensive to trainThey are prone to overfittingThey require labeled data for trainingThey are not suitable for high-dimensional data

What is a significant disadvantage of decision trees?Answer areaThey are difficult to interpretThey require a lot of dat preprocessingThey are prone to overfittingThey are not suitable for categorical data

Which of the following is a disadvantage of the decision tree algorithm for classification?It is not suitable for handling large datasets.It cannot handle missing values in the dataset.It requires the data to be linearly separable.It is prone to overfitting with complex trees.

What are the disadvantages of the decision tree?*1 point(A) Over-fitting of the data is possible.(C) We have to balance the dataset before training the model(B) The small variation in the input data can result in a different decision tree(D) All of the above