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MACHINE LEARNINGNaive Bayes assumes (i) Features are dependent (ii) Features are independent given the class (iii) Class probabilities are equal (iv) No prior knowledge is required20252mData MiningWhy is naive Bayesian classification called 'naive'? Briefly outline the major ideas of naive Bayesian classification.20227mMACHINE LEARNINGWrite short notes on any two of the following: (a) Naive Bayes (b) Logistic Regression \(c\) Back Propagation algorithm202314mData MiningExplain Naive Bayesian classification algorithm.20207m
PreviousWhich of the following steps/assumptions in regression modeling impacts the trade-off between under-fitting and over-fitting the most? (i) The polynomial degree (ii) Whether we learn the weights by matrix inversion or gradient descent (iii) The use of a constant-term (iv) None of the aboveNextThe feature of ANN in which ANN creates its own organization or representation of information it receives during learning time is (i) adaptive learning (ii) self-organization (iii) what-if analysis (iv) supervised learning