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Data MiningBayesian classifiers is (i) a class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory (ii) any mechanism employed by a learning system to constrain the search space of a hypothesis (iii) an approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation (iv) None of the above20202mMACHINE LEARNINGDiscuss with examples of instance-based learning algorithms.20237mArtificial intelligenceWhat do you mean by learning? Explain briefly the learning methods. Discuss the advantages and disadvantages of rule-based system.20227mData MiningDefine Classification and Prediction in data mining. Describe the concept of Bayesian Classification with a simple example.20257m
PreviousBackground knowledge referred to (i) additional acquaintance used by a learning algorithm to facilitate the learning process (ii) a neural network that makes use of a hidden layer (iii) it is a form of automatic learning (iv) None of the aboveNextSome telecommunication companies want to segment their customers into distinct groups in order to send appropriate subscription offers. This is an example of (i) supervised learning (ii) data extraction (iii) serration (iv) unsupervised learning