C4.5: programs for machine learning
C4.5: programs for machine learning
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
Machine Learning
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Finding Relevant Biomolecular Features
Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology
A Comparison of Noise Handling Techniques
Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference
Noise Elimination in Inductive Concept Learning: A Case Study in Medical Diagnosois
ALT '96 Proceedings of the 7th International Workshop on Algorithmic Learning Theory
Polishing Blemishes: Issues in Data Correction
IEEE Intelligent Systems
Support Vector Machine for Outlier Detection in Breast Cancer Survivability Prediction
Advanced Web and NetworkTechnologies, and Applications
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Osteogenesis Imperfecta (OI) is a genetic collagenousdisease associated with mutations in one or both of thegenes COLIA1 and COLIA2. There are at least four knownphenotypes of OI, of which type II is the severest and oftenlethal. We identified three approaches to noise handling,namely, robust algorithms, filtering, and polishing,and evaluated their effectiveness when applied to the problemof classifying the disease OI based on a data set ofamino acid sequences and associated information of pointmutations of COLIA1. Preliminary results suggest that eachnoise handling mechanism can be useful under different circumstances.Filtering is stable across all cases. Pruningwith robust c4.5 increased the classification accuracy insome cases, and polishing gave rise to some additional improvementin classifying the lethal OI phenotype.