Machine Learning Interview Questions and Answers
Question - 111 : - What do you understand by Precision and Recall?
Answer - 111 : -
In pattern recognition, The information retrieval and classification in machine learning are part of precision. It is also called as positive predictive value which is the fraction of relevant instances among the retrieved instances.
Recall is also known as sensitivity and the fraction of the total amount of relevant instances which were actually retrieved.
Both precision and recall are therefore based on an understanding and measure of relevance.
Question - 112 : - What are collinearity and multicollinearity?
Answer - 112 : -
Collinearity is a linear association between two predictors. Multicollinearity is a situation where two or more predictors are highly linearly related.
Question - 113 : - What is the difference between Entropy and Information Gain?
Answer - 113 : -
The information gain is based on the decrease in entropy after a dataset is split on an attribute. Constructing a decision tree is all about finding the attribute that returns the highest information gain (i.e., the most homogeneous branches). Step 1: Calculate entropy of the target.