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5. (F) Maximizing The Likelihood Of Logistic Regression Model Yields Multiple Local Optimums. 6. (F) No Classifier Can Do Better Than A Naive Bayes Classifier If The Distribution Of The Data Is Known. 7. (F) The Back-propagation Algorithm Learns A Globally Optimal Neural Network With Hidden Layers. 8. 3th, 2024
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