Improving SVM accuracy by training on auxiliary data sources.

Pengcheng Wu Thomas G. Dietterich

Published in: ICML (2004)

Keyphrases

data sources
training speed
training process
training set
classification performances
support vector machine svm
high accuracy
training algorithm
classification accuracy
support vector

support vector machine
knn
fold cross validation
training set size
svm training
multi class
training examples
prediction accuracy
random selection

error rate
noise tolerance
kernel svms
generalization ability
feature vectors
feature space
classification algorithm
training dataset
support vectors

multi class classification
database
stochastic gradient descent
computational cost
data model
training data
machine learning
labeling effort
databases