Analysis of SEER Dataset for Breast Cancer Diagnosis using C4.5 Classification Algorithm
K.Rajesh, Dr. Sheila Anand, PG Student, Dean (Research) Computer Studies
Breast Cancer Diagnosis, Classification, Clinical Data, SEER Dataset, C4.5 Algorithm
Abstract: Medical professionals need a reliable prediction methodology to diagnose cancer and distinguish between the different stages in cancer. Classification is a data mining function that assigns items in a collection to target groups or classes. C4.5 classification algorithm has been applied to SEER breast cancer dataset to classify patients into either "Carcinoma in situ" (beginning or pre-cancer stage) or "Malignant potential". Random test samples have been selected from the pre-processed data to obtain classification rules. The rule set obtained was tested with the remaining data. The results are presented and discussed.
Keywords: Breast Cancer Diagnosis, Classification, Clinical Data, SEER Dataset, C4.5 Algorithm
How to Cite:
[1] K.Rajesh, Dr. Sheila Anand, PG Student, Dean (Research) Computer Studies, βAnalysis of SEER Dataset for Breast Cancer Diagnosis using C4.5 Classification Algorithm,β International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)
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