Define following terms. 1. Information gain 2. DBSCAN 3. Reinforcement learning
[3 marks]What is human learning? Explain types of human learning.
[4 marks]Discuss the applications and tools of machine learning.
[7 marks]Explain qualitative and quantitative data in machine learning.
[3 marks]What are activities involved in machine learning?
[4 marks]Explain k-fold cross validation method in detail
[7 marks]Briefly explain overall feature selection process.
Discuss singular value decomposition algorithm.
[7 marks]What is feature transformation? Explain feature construction process in detail.
[7 marks]Define outliers. Can we handle outliers and missing values in data? Explain in brief.
[7 marks]Define over-fitting & under-fitting. Discuss the errors in learning.
[7 marks]Briefly explain classification learning steps.
[7 marks]Explain multiple linear regression technique in detail.
[7 marks]What is ensembling? Explain random forest model in brief.
[7 marks]Differentiate supervised learning and unsupervised learning with reference to various aspects.
[7 marks]Explain k-means clustering algorithm in detail.
[7 marks]What is regression? Discuss assumptions in regression analysis.
[7 marks]What is association rule? Discuss the concept of support and confidence to justify the strength of association rule with appropriate example.
[7 marks]Explain k-medoids clustering algorithm in detail.
[7 marks]