<--- Back to Details
First PageDocument Content
Linear classifier / Normal distribution / Perceptron / Support vector machine / Variance / AdaBoost / Supervised learning / Statistics / Statistical classification / Machine learning
Date: 2009-02-15 15:01:42
Linear classifier
Normal distribution
Perceptron
Support vector machine
Variance
AdaBoost
Supervised learning
Statistics
Statistical classification
Machine learning

Confidence-Weighted Linear Classification Mark Dredze Koby Crammer

Add to Reading List

Source URL: www.cs.jhu.edu

Download Document from Source Website

File Size: 324,70 KB

Share Document on Facebook

Similar Documents

Machine learning / Artificial intelligence / Learning / Statistics / Mixture model / Log-linear model / Pattern recognition / K-means clustering / Linear classifier

WEYAND, DESELAERS, NEY: LOG-LINEAR MIXTURES 1 Log-Linear Mixtures for Object Class Recognition

DocID: 1rsoW - View Document

Machine learning / Artificial intelligence / Statistical classification / Learning / Ensemble learning / Cybernetics / Boosting / Support vector machine / Linear classifier / Naive Bayes classifier / Online machine learning / Generalization error

A Few Useful Things to Know about Machine Learning Pedro Domingos Department of Computer Science and Engineering University of Washington Seattle, WA, U.S.A.

DocID: 1rgDn - View Document

Machine learning / Microarrays / Statistical classification / Biology / Statistics / Support vector machine / Polynomial kernel / Affymetrix / Linear classifier / DNA microarray / Kernel method / Gene expression profiling

264 Genome Informatics 13: 264–Characteristics of Support Vector Machines in Gene Expression Analysis

DocID: 1rf4U - View Document

Statistical classification / Mathematical analysis / Analysis / Mathematics / Ensemble learning / Mathematical optimization / Linear algebra / Convex analysis / Support vector machine / Linear classifier / Norm / AdaBoost

LNAICatenary Support Vector Machines

DocID: 1qVOf - View Document

Machine learning / Statistical classification / Artificial intelligence / Learning / Support vector machine / Pattern recognition / Supervised learning / Linear classifier / Naive Bayes classifier / Generalization error / Document classification

Towards Anytime Active Learning: Interrupting Experts to Reduce Annotation Costs Maria E. Ramirez-Loaiza Aron Culotta

DocID: 1qK0H - View Document