Breast cancer disease classification using fuzzy-ID3 algorithm based on association function

Breast cancer is the second leading cause of mortality among female patients worldwide. Early detection breast considerd as one most effective ways to prevent disease from spreading and enable human can make correct decision on next process. Automatic diagnostic methods were frequently used conduct diagnoses in order increase accuracy speed detection. The fuzzy-ID3 algorithm with association function implementation (FID3-AF) proposed a classification technique for FID3-AF hybridisation fuzzy system, iterative dichotomizer 3 (ID3) algorithm, function. fuzzy-neural dynamicbottleneck-detection (FUZZYDBD) considered an automatic database definition method, would aid development data fuzzification process FID3-AF. overcame ID3’s issue being unable handle continuous data. implemented minimise overfitting enhance generalisation ability. results indicated that robust classification. A thorough comparison numerous existing was conducted validate method’s competency. This study established performed well outperform other