Statistical analysis with missing data
Statistical analysis with missing data
C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning - Special issue on applications in molecular biology
Discovering data mining: from concept to implementation
Discovering data mining: from concept to implementation
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
SPRINT: A Scalable Parallel Classifier for Data Mining
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Discovering the Primary Factors of Cancer from Health and Living Habit Questionnaires
DS '99 Proceedings of the Second International Conference on Discovery Science
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This paper describes how data mining is being used to identify primary factors of cancer incidences and living habits of cancer patients from a set of health and living habit questionnaires. Decision tree, radial basis function and back propagation neural network have been employed in this case study. Decision tree classification uncovers the primary factors of cancer patients from rules. Radial basis function method has advantages in comparing the living habits between a group of cancer patients and a group of healthy people. Back propagation neural network contributes to elicit the important factors of cancer incidences. This case study provides a useful data mining template for characteristics identification in healthcare and other areas.