Introduction CptS 570 Machine Learning School of EECS Washington State University
What is Learning? Webster � To gain knowledge or understanding of or skill in by study, instruction or � experience To memorize � Synonym: discover � To obtain knowledge of for the first time � May imply acquiring knowledge with little effort or conscious intention (as by � simply being told) or it may imply study and practice Knowledge � Knowing something with familiarity gained through experience or association � Facts or ideas acquired by study, investigation, observation, or experience � Deduction? (n!) � Knowledge representation? � Performance measure? �
What is Machine Learning? � Herbert Simon, CMU � Any process by which a system improves its performance � Expert systems � Acquisition of explicit knowledge � Psychologists � Skill acquisition � Scientists � Theory formation, hypothesis formation and inductive inference � Tom Mitchell, CMU � A computer program that improves its performance at some task through experience
Motivations � Automated knowledge engineering � Expertise is scarce � Codification of expertise is difficult � Expertise frequently consists of a set of test cases � Data from measurements, but no information or knowledge � Only one computer has to learn, then copy � Discover new knowledge � Understand human learning
Applications � Speech recognition � Object recognition � Language learning � Autonomous navigation � Data mining � Intelligent agents � Cognitive modeling
History � Exploration (1950s and 1960s) � Neurophysiological � Rosenblatt's perceptron � Biological � Simulated evolution � Psychological � Symbol processing systems � Statistical � Control and pattern recognition � Samuel's checkers program � Theoretical � Gold's identification in the limit � Minsky and Papert's criticism of the perceptron
History � Development of practical algorithms (1970s) � Winston's ARCH � Learned concept of a blocks-world arch � Buchanan and Mitchell's Meta-Dendral � Learned mass-spectrometry prediction rules � Michalski's AQ11 � Learned soybean disease diagnosis rules � Quinlan's ID3 � Learned chess end-game rules � Fikes, Hart and Nilsson's MACROPS � Learned macro-operators in blocks-world planning � Lenat's AM � Discovered interesting mathematical concepts
History � Explosion of research directions (1980s) � Learning theory � Symbolic learning algorithms � Connectionist (neural network) learning algorithms � Clustering and discovery � Explanation-based learning � Knowledge-guided inductive learning � Analogical and case-based reasoning � Genetic algorithms
History � Maturity of the field (1990s) � Statistical comparisons of algorithms � Theoretical analyses of algorithms � Machine learning = Data mining (?) � Successful applications � Multi-relational learning � Ensemble and Kernel Methods
Mitchell’s Book � Practical approach to study of machine learning � Methodology snapshot (good one for 1997)
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