The role of Occam's razor in knowledge discovery
P Domingos - Data mining and knowledge discovery, 1999 - Springer
Many KDD systems incorporate an implicit or explicit preference for simpler models, but this
use of “Occam's razor” has been strongly criticized by several authors (eg, Schaffer, 1993; …
use of “Occam's razor” has been strongly criticized by several authors (eg, Schaffer, 1993; …
Taxonomy for characterizing ensemble methods in classification tasks: A review and annotated bibliography
L Rokach - Computational statistics & data analysis, 2009 - Elsevier
Ensemble methodology, which builds a classification model by integrating multiple
classifiers, can be used for improving prediction performance. Researchers from various …
classifiers, can be used for improving prediction performance. Researchers from various …
Ensemble-based classifiers
L Rokach - Artificial intelligence review, 2010 - Springer
The idea of ensemble methodology is to build a predictive model by integrating multiple
models. It is well-known that ensemble methods can be used for improving prediction …
models. It is well-known that ensemble methods can be used for improving prediction …
[图书][B] Data mining with decision trees: theory and applications
Decision trees have become one of the most powerful and popular approaches in
knowledge discovery and data mining; it is the science of exploring large and complex …
knowledge discovery and data mining; it is the science of exploring large and complex …
Rule induction with CN2: Some recent improvements
P Clark, R Boswell - Machine Learning—EWSL-91: European Working …, 1991 - Springer
The CN2 algorithm induces an ordered list of classification rules from examples using
entropy as its search heuristic. In this short paper, we describe two improvements to this …
entropy as its search heuristic. In this short paper, we describe two improvements to this …
Selecting a classification method by cross-validation
C Schaffer - Machine learning, 1993 - Springer
If we lack relevant problem-specific knowledge, cross-validation methods may be used to
select a classification method empirically. We examine this idea here to show in what …
select a classification method empirically. We examine this idea here to show in what …
[图书][B] Pattern classification using ensemble methods
L Rokach - 2009 - books.google.com
Researchers from various disciplines such as pattern recognition, statistics, and machine
learning have explored the use of ensemble methodology since the late seventies. Thus …
learning have explored the use of ensemble methodology since the late seventies. Thus …
An intelligent prediction system for educational data mining based on ensemble and filtering approaches
The ensemble approach such as boosting is based on heuristic system to develop
prediction paradigms. The ensemble learning techniques are typically more accurate than …
prediction paradigms. The ensemble learning techniques are typically more accurate than …
Inductive and Bayesian learning in medical diagnosis
I Kononenko - Applied Artificial Intelligence an International …, 1993 - Taylor & Francis
Although successful in medical diagnostic problems, inductive learning systems were not
widely accepted in medical practice. In this paper two different approaches to machine …
widely accepted in medical practice. In this paper two different approaches to machine …
[图书][B] Ensemble learning: pattern classification using ensemble methods
L Rokach - 2019 - World Scientific
Artificial intelligence (AI) is a scientific discipline that aims to create intelligent machines.
Machine learning is a popular and practical AI subfield that aims to automatically improve …
Machine learning is a popular and practical AI subfield that aims to automatically improve …