On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach (1997)

by Steven L. Salzberg , Usama Fayyad
Venue:Data Mining and Knowledge Discovery
Citations:172 - 0 self

Active Bibliography

1 Methodological Note On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach – - 1996
Machine Learning: An Annotated Bibliography for the 1995 AI & . . . – - 1995
87 Unifying instance–based and rule–based induction – - 1996
7 Constructing New Attributes for Decision Tree Learning – - 1996
35 Classification and Regression using Mixtures of Experts – - 1997
3 Comparative Experiments on Disambiguating Word Senses: . . . – - 1996
107 Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning – - 1996
147 Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey – - 1997
12 A comprehensive case study: An examination of machine learning and connectionist algorithms – - 1995
k. Results indicate that this procedure is very effective in estimating good feature weights (Table 4.8). Particularly the results obtained in the – - 1994
50 Neural networks for classification: a survey – - 2000
13 Pruning decision trees and lists – - 2000
60 Rule Induction and Instance-Based Learning: A Unified Approach – - 1995
2 Conservation of Generalization: A Case Study – - 1995
25 Small Sample Statistics for Classification Error Rates I: Error Rate Measurements – - 1996
13 A Benchmark For Classifier Learning – - 1993
The PNC 2 Cluster Algorithm - An integrated learning algorithm for rule induction – - 2003
38 Simplifying Decision Trees: A Survey – - 1996
15 Evaluating Machine Learning Models for Engineering Problems – - 1999