CptS 570 – Machine Learning School of EECS Washington State University CptS 570 - Machine Learning 1
Course overview What is machine learning? Why do machine learning? Applications Approaches Resources CptS 570 - Machine Learning 2
Objectives ◦ Knowledge of machine learning (ML) foundations, paradigms and algorithms ◦ Techniques for evaluating ML algorithms ◦ Practical experience using ML algorithms ◦ Current ML issues Website ◦ www.eecs.wsu.edu/~holder/courses/CptS570.html CptS 570 - Machine Learning 3
Assignments ◦ Readings ◦ Six (6) homeworks (40%) ◦ Two (2) exams (20%) ◦ Project (20%) ◦ Presentation (10%) ◦ Critiques and class participation (10%) CptS 570 - Machine Learning 4
Textbook ◦ Ethem Alpaydin (2010). Introduction to Machine Learning, Second Edition. MIT Press. ◦ www.cmpe.boun.edu.tr/~ethem/i2ml2e CptS 570 - Machine Learning 5
What is learning? What is machine learning? CptS 570 - Machine Learning 6
Webster ◦ Gain knowledge or understanding of or Sleep learning? skill in by study, instruction or experience (www.links999.net) ◦ Memorize ◦ Synonym: Discovery 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 CptS 570 - Machine Learning 7
Herbert Simon (1970) ◦ Any process by which a system improves its performance. Tom Mitchell (1990) ◦ A computer program that improves its performance at some task through experience. Ethem Alpaydin (2010) ◦ Programming computers to optimize a performance criterion using example data or past experience. CptS 570 - Machine Learning 8
How is knowledge represented? How is experience represented? What is the performance measure? Knowledge acquisition vs. skill acquisition Is deduction learning? CptS 570 - Machine Learning 9
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 Systems need to adapt to unknown, dynamic environments CptS 570 - Machine Learning 10
Patient cases [medical knowledge] automated (better?) diagnosis Autonomous driving Speech recognition Recommendations (Amazon, Netflix) Prediction (business, financial, environment, health, energy, …) Fraud/intrusion detection CptS 570 - Machine Learning 11
Statistics Pattern recognition Signal processing Control Artificial intelligence Data mining Neuroscience Cognitive science Psychology CptS 570 - Machine Learning 12
Supervised Learning ◦ Classification ◦ Regression Unsupervised Learning ◦ Clustering Reinforcement Learning CptS 570 - Machine Learning 13
D Default e b Good Status t Income CptS 570 - Machine Learning 14
Default Good Status D e b t If Income < t Then Default t Income CptS 570 - Machine Learning 15
No Loan Default Good Status D e b t if Debt < a*Income + b then Loan else No Loan Loan Income CptS 570 - Machine Learning 16
Cluster 2 Cluster 1 D e Categories b 1) Debt exceeds t Income 2) High Debt, Cluster 3 High Income 3) Low Debt Income CptS 570 - Machine Learning 17
No Loan Debt<50 yes no no D e Income Income b t 50- 50 >100 >100 <50 50- 50 <50 >100 >100 100 100 100 100 Loan NO YES YES NO NO YES Income CptS 570 - Machine Learning 18
Input Hidden Outpu put Layer Layer Layer No Loan 0.123 23 0.117 17 Debt Loan D e No No Income me b Loan t 0.203 03 0.545 45 Loan Income CptS 570 - Machine Learning 19
Evaluation ◦ Which learning approach is better Theoretical bounds ◦ What is and is not learnable Scalability ◦ Learning from massive datasets CptS 570 - Machine Learning 20
Software ◦ Weka (www.cs.waikato.ac.nz/~ml/weka) ◦ Machine learning open-source software (mloss.org) Data ◦ UCI ML Repository (archive.ics.uci.edu/ml) ◦ UCI KDD Repository (kdd.ics.uci.edu) ◦ Challenges: KDD- Cup, Netflix, … CptS 570 - Machine Learning 21
Conferences ◦ International Conference on Machine Learning (ICML) ◦ Knowledge Discovery and Data Mining (KDD) ◦ IEEE Conference on Data Mining (ICDM) ◦ SIAM Data Mining Conference (SDM) ◦ Association for the Advancement of AI (AAAI) ◦ International Joint Conference on AI (IJCAI) ◦ Many more … CptS 570 - Machine Learning 22
Journals ◦ Machine Learning Journal ◦ Journal of Machine Learning Research ◦ Data Mining and Knowledge Discovery ◦ Many more … WWW ◦ www.kdnuggets.com (subscribe!) CptS 570 - Machine Learning 23
Machine learning is a computational process that improves performance based on experience. Numerous successful methods Maturing theory Open and active research area CptS 570 - Machine Learning 24
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