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Data MiningDifferentiate between Partitioning and Hierarchical Clustering methods. Explain Outlier Analysis and its importance in data mining.20257mData MiningClassification is a process of: (i) Assigning data to predefined classes (ii) Dividing data into clusters (iii) Summarizing data (iv) Cleaning data20252mData MiningCluster is (i) group of similar objects that differ significantly from other objects (ii) operations on a database to transform or simplify data in order to prepare it for a machine learning algorithm (iii) symbolic representation of facts or ideas from which information can potentially be extracted (iv) None of the above20202mData MiningOutlier are (i) legitimate data objects (ii) illegitimate data objects (iii) legitimate and illegitimate data objects (iv) None of the above20222m
Previous(a) Who is called the father of Machine Learning? (i) Geoffrey Hill (ii) Geoffrey Chaucer (iii) Geoffrey Everest Hinton (iv) Tom MitchellNext\(c\) In what type of learning labelled training data is used : (i) unsupervised learning (ii) supervised learning (iii) reinforcement learning (iv) active learning