Feature Selection Using Genetic Algorithm for Cancer Prediction System
作者： Rupali , Rupali Verma , Rohit Handa , Veena Puri
DOI: 10.1007/978-981-15-5341-7_91
关键词: Feature selection 、 Cancer 、 k-nearest neighbors algorithm 、 Breast cancer 、 Computer science 、 Machine learning 、 Genetic algorithm 、 Prediction system 、 Artificial intelligence 、 Early prediction
摘要: In healthcare sector, cancer is one of the most threatening and fast-growing diseases. The early diagnosis this disease very important as success rate its treatment depends upon how accurately it diagnosed. machine learning algorithms are helpful in detection prediction To improve efficiency these algorithms, optimal features need to be selected. So, research work uses genetic algorithm select before applying k-nearest neighbor (KNN) weighted (WKNN) on Wisconsin Breast Cancer Prognosis dataset extracted from UCI repository. This approach helps results show that WKNN performed better with 86.44% accuracy than KNN which gives 83.05% accuracy.
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