Solve with machine learning python Question 11 write in detail : Discuss two different ways of controlling overfitting i

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Solve with machine learning python
Question 11 write in detail : Discuss two different ways ofcontrolling overfitting in decision trees.
Question 12 Suppose you have been asked to use a Support VectorClassifier on data that is not linearly separable. Would that bepossible? If 50, how?
Question 13 What is the main issue that hinders theapplicability of kNN non-parametric learning?
Question 14 What method trains more classifiers, One-vs-One, orOne-vs-Rest? Does that mean that is is also more computationallyexpensive? Justify your answer.
Question 15 Name two different non-linear classifiers we havediscussed in the class.
Question 18 Model-1 is a logistic neuron with weights: (w1 = 1,w2 = 1, w3 = 3, b = -2]
Model-2 is a support vector classifier with weights: (w1 =-2,w2=-2, w3 = -6, b = 4]
Given a test point x, Model-1 and Model-2 will give: (pick thecorrect answers) O Opposite predictions O Identical predictions (It depends on x