Back to Search
Start Over
Generating concise and accurate classification rules for breast cancer diagnosis
- Source :
- Artificial intelligence in medicine. 18(3)
- Publication Year :
- 2000
-
Abstract
- In our previous work, we have presented an algorithm that extracts classification rules from trained neural networks and discussed its application to breast cancer diagnosis. In this paper, we describe how the accuracy of the networks and the accuracy of the rules extracted from them can be improved by a simple pre-processing of the data. Data pre-processing involves selecting the relevant input attributes and removing those samples with missing attribute values. The rules generated by our neural network rule extraction algorithm are more concise and accurate than those generated by other rule generating methods reported in the literature.
- Subjects :
- Artificial neural network
Computer science
business.industry
Extraction algorithm
Medicine (miscellaneous)
Feature selection
Pattern recognition
Breast Neoplasms
computer.software_genre
medicine.disease
Diagnosis, Differential
Breast cancer
Artificial Intelligence
medicine
Humans
Female
Data mining
Artificial intelligence
Data pre-processing
Neural Networks, Computer
Differential (infinitesimal)
business
computer
Algorithms
Subjects
Details
- ISSN :
- 09333657
- Volume :
- 18
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Artificial intelligence in medicine
- Accession number :
- edsair.doi.dedup.....98cba7687fb788859b39849593cf16c8