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Small change to training set causes large change in output hypothesis ... P[j] Combiner-Stacked-Gen (Train-Set[j], L, k, n, m', Levels - 1) ELSE // Base case: 1 level ...
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Output of unit: threshold (activation) function on net input (threshold = w0) ... Nonlinear activation (aka transfer, squashing) function: generalization of sgn ...
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Let h denote the number of heads in experiment xi (a single data point) ... Molecular biology: pre-clustering DNA acceptor, donor sites (mouse, human) ...
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Cluster definition. EM, AutoClass, Principal Components Analysis, ... Cluster analysis: study of algorithms, methods for ... Cluster: Informal and ...
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Kansas State University. Department of Computing and Information Sciences ... P: percent of games won in world tournament. E: opportunity to play against self ...
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CIS 732: Machine Learning and Pattern Recognition. KSU ... bread, shoes, clothes. The user-specified MIS values are as follows: MIS(bread) = 2% MIS(shoes) = 0.1 ...
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Kansas State University. Department of Computing and Information Sciences ... BBN model for patient monitoring in surgical anesthesia ...
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How to Select 'Best' Model (Tree) ... Infer T from D (using ID3) - grow until D is fit as well as possible (allow overfitting) Convert T into equivalent set of ...
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Department of Computing and Information Sciences ... Choosing New Examples. Next Week ... Classify x based on S set. Kansas State University ...
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T: play games of checkers. P: percent of games won in world tournament ... x1 = Sunny, Warm, High, Strong, Cool, Same x2 = Sunny, Warm, High, Light, Warm, Same ...
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Most popular heuristic. Developed by J. R. Quinlan. Based on information gain ... Use heuristic (figure of merit that guides search) Use greedy algorithm ...
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Have mechanical operators (F) for finding logically entailed conclusions (C) ... Use this to reason over logical statements (propositions, first-order clauses) ...
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Rapidly growing volume of online data from various sources. Available computational power ... Test set: 12/20 = 0.600. Neural Network Learning ...
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Overview of Bayesian Learning ... Bayesian belief network (BBN) structure learning and parameter estimation ... Stochastic Bayesian learning: Markov chain Monte ...
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'Bagging, Boosting, and C4.5', Quinlan. Section 5, 'MLC ... Hierarchical mixture models: divide-and-conquer estimation method. Kansas State University ...
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Kansas State University. Department of Computing and Information Sciences ... H Build-Heap (E, Weights) // aka priority queue (|E ...
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Methodology (model parameters): aj, uij, bk, vjk (hyperparameters) ... Hidden layer activation: hj (x) = tanh (aj i uij xi) Classifier Output: Prediction ...
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Instances (unlabeled examples): represented as attribute ('feature') vectors ... Main Decision: Next Attribute to Condition On ... Partitioning on Attribute Values ...
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Suggested Exercises: 18.3, Russell and Norvig; 3.1, Mitchell ... Top-down induction of decision trees. Calculating reduction in entropy (information gain) ...
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Office hours: after class Mon/Wed/Fri; other times by appointment ... All students (especially remote students): post in class web board ...
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Fastest way to reach instructor: instant messaging (ICQ, MSN Messenger) ... comp.os.ms-windows.misc rec.autos talk.politics.guns sci.crypt ...
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... g. typewriter metaphor in word processing but Japanese and Chinese rarely used ... Symbols meaning may be culturally dependent ...
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The Winnow. Another linear threshold model. Learning algorithm and training rule ... Idea: use a Winnow - perceptron-type LTU model (Littlestone, 1988) ...
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Kansas State University. Department of Computing and Information Sciences ... with m examples of c is less than | H | (1 - )m , Quod Erat Demonstrandum ...
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Winnow Algorithm Learns Linear Threshold (LT) Functions. Converting to Disjunction Learning ... Supports multiple ANN architectures and training algorithms ...
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Department of Computing and Information Sciences, KSU ... Caveats: partially observable state, uncertainty (measurement error, etc. ...
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Kansas State University. Department of Computing and Information Sciences. CIS 732: Machine Learning and ... Duality: data fusion problem redistribution ...
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Kansas State University. Department of Computing and Information Sciences. CIS 732: Machine Learning and Pattern ... Futility of learning without bias ...
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