Μηχανική Μάθηση
Topic outline
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Machine learning as a field, clinical bioinformatics, text classification, spam detection, mind reading, autonomous systems, supervised learning, unsupervised learning, reinforcement learning, the problem of induction, model space, inductive bias, classification versus regression.
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Hypotheses in machine learning, stochasticity, proving an hypothesis, the null hypothesis, test statistics, standard single hypothesis testing, rejection regions, rejection procedure, statistical errors, statistical significance, p-values.
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By Tom M. Mitchell. Focus only on slides regarding Naive Bayes.
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Lecture by Adele Cutler.
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1- Nearest Neighbor, K-Nearest Neighbor (KNN), cross validation, distance-weighted KNN, locally weighted averaging, locally weighted regression, euclidean distance, weighted euclidean distance, information gain, memory based methods.
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Hypothesis testing
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