64 search results - page 3 / 13 » On the Boosting Ability of Top-Down Decision Tree Learning A... |
IFIP12
2008
13 years 9 months ago
2008
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
ECAI
2008
Springer
13 years 9 months ago
2008
Springer
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
MMB
2012
Springer
12 years 3 months ago
2012
Springer
Abstract. During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with h...
ICML
2000
IEEE
14 years 8 months ago
2000
IEEE
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...