<--- Back to Details
First PageDocument Content
Cluster analysis / Multivariate statistics / Statistical classification / K-means clustering / Support vector machine / Spectral clustering / Expectation–maximization algorithm / Kernel methods / Mixture model / Statistics / Machine learning / Geostatistics
Date: 2011-10-29 18:02:04
Cluster analysis
Multivariate statistics
Statistical classification
K-means clustering
Support vector machine
Spectral clustering
Expectation–maximization algorithm
Kernel methods
Mixture model
Statistics
Machine learning
Geostatistics

doi:[removed]j.patcog[removed]

Add to Reading List

Source URL: profs.sci.univr.it

Download Document from Source Website

File Size: 174,04 KB

Share Document on Facebook

Similar Documents

Support Vector Machines and Kernel Methods Shrey Gupta Applied Machine Learning (HOUSECS 59-01), Duke University October 10, 2018

DocID: 1uA0f - View Document

[Zaid Harchaoui, Francis Bach, Olivier Cappé, and Éric Moulines] Kernel-Based Methods for Hypothesis

DocID: 1ueSP - View Document

MULTI-SCALE KERNEL METHODS FOR CLASSIFICATION Nick Kingsbury∗ , David B H Tay† , M Palaniswami‡ University of Cambridge∗ , Dept. of Engineering, Cambridge, U.K. LaTrobe University† , Dept. of EE, Victoria, Aust

DocID: 1ueeE - View Document

An Empirical Study on The Properties of Random Bases for Kernel Methods Maximilian Alber, Pieter-Jan Kindermans, Kristof T. Schütt Technische Universität Berlin Klaus-Robert Müller

DocID: 1tHy5 - View Document

Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand Influence Function Yong Liu Shali Jiang Shizhong Liao

DocID: 1tjw8 - View Document