Answer following: 1. List the characteristics of good dataset. 2. Avalue to be predicted in machine learning is called as ___________. 3. Machine learning is a branch of _______________. 4. Predicting the monthly sales of store is ______________ task. (Regression/Classification) 5. State the applications of R. 6. What is the hamming distance between 10101011 & 01010101? 7. Define slope.
[7 marks]Explain precision and recall in terms of evaluating performance of model.
[4 marks]Discuss eager learner and lazy learner.
[3 marks]Define machine learning. Discuss reinforcement learning in brief.
[7 marks]Write short note on: 1. Descriptive Models 2. Histogram
[7 marks]Explain hold-out method for training a model.
[7 marks]Discuss the concept of ensembling of models.
[7 marks]Explain the process of encoding categorical variables.
[7 marks]Explain the measures of feature redundancy.
[7 marks]Explain types of feature selection approaches.
[7 marks]Explain multiple linear regression in detail.
[7 marks]Discuss following: 1. Entropy of decision tree 2. Information gain of decision tree
[7 marks]Write and discuss KNN algorithm with its strength, weakness and applications.
[7 marks]What is regression? Explain logistic regression.
[7 marks]Define hyperplane. Explain SVM in detail.
[7 marks]Explain hierarchical clustering algorithm with its applications.
[7 marks]Explain following with reference to association rules. 1. Support 2. Confidence
[4 marks]Explain density based clustering algorithm.
[3 marks]Explain k-means clustering algorithm in detail.
[7 marks]