Ch.5 Classification and Clustering Classification [Book, scattered] With discrete response variables, do classification instead of regression. (b) 1

First Page		Document Content
Date: 2013-09-30 19:02:28 Statistical classification Bayesian statistics Regression analysis Linear classifier Posterior probability Linear regression Marginal distribution K-nearest neighbor algorithm Expected value Statistics Econometrics Machine learning		Ch.5 Classification and Clustering Classification [Book, scattered] With discrete response variables, do classification instead of regression. (b) 1 Add to Reading List Source URL: www.ocgy.ubc.ca Download Document from Source Website File Size: 522,77 KB Share Document on Facebook

	MEMOCODE 2014 Design Contest: k-Nearest Neighbors with Mahalanobis Distance Metric Peter Milder Department of Electrical and Computer Engineering Stony Brook University Stony Brook, NY 11794–2350 DocID: 1rmvj - View Document
	A Collaborative Filtering Approach to Real-Time Hand Pose Estimation Chiho Choi, Ayan Sinha, Joon Hee Choi, Sujin Jang, Karthik Ramani Purdue University West Lafayette, IN 47907, USA {chihochoi, sinha12, choi240, jang64, DocID: 1rkoE - View Document
	Dynamic Euclidean Minimum Spanning Trees and Extrema of Binary Functions David Eppstein Department of Information and Computer Science University of California, Irvine, CA 92717 DocID: 1qXBI - View Document
	Mach Learn DOIs10994Visualizing non-metric similarities in multiple maps Laurens van der Maaten · Geoffrey Hinton DocID: 1qSlY - View Document
	Selective Hashing: Closing the Gap between Radius Search and k-NN Search Jinyang Gao‡ H. V. Jagadish§ DocID: 1qNhe - View Document