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ML
2000
ACM
185views Machine Learning» more  ML 2000»
14 years 11 months ago
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
Twenty-two decision tree, nine statistical, and two neural network algorithms are compared on thirty-two datasets in terms of classification accuracy, training time, and (in the ca...
Tjen-Sien Lim, Wei-Yin Loh, Yu-Shan Shih
TKDE
2008
133views more  TKDE 2008»
14 years 11 months ago
Rotational Linear Discriminant Analysis Technique for Dimensionality Reduction
The linear discriminant analysis (LDA) technique is very popular in pattern recognition for dimensionality reduction. It is a supervised learning technique that finds a linear tran...
Alok Sharma, Kuldip K. Paliwal
FUIN
2002
132views more  FUIN 2002»
14 years 11 months ago
RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...
Grzegorz Góra, Arkadiusz Wojna
96
Voted
ECAI
2004
Springer
15 years 5 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
ISSRE
2007
IEEE
15 years 1 months ago
Data Mining Techniques for Building Fault-proneness Models in Telecom Java Software
This paper describes a study performed in an industrial setting that attempts to build predictive models to identify parts of a Java system with a high probability of fault. The s...
Erik Arisholm, Lionel C. Briand, Magnus Fuglerud