… two techniques of machine learning for classification of breast … cancer database. The purpose
of this article is developing effective machine learning approaches for cancer classification …

… diagnosis Breast Cancer. Results: After comparing the machine learning algorithms efficiency,
… regression gave the best results with an accuracy of 98% for breast cancer classification. …

… Diagnostic Breast Cancer (WDBC) Dataset. The focus of this paper is to integrate these
machine learning techniques with feature selection/feature extraction methods and compare …

… The study [46] utilized a deep learning approach to classify breast cancer images, convolution
neural network algorithm was employed CNN. The study evaluated the method by using …

… to comprehend the different categories of machine acquiring knowledge systems along with
… of machine learning, including cancer classification, and how machine learning algorithms …

… Data was collected from the UCI machine learning respiratory, … transfer function has the
highest classification accuracy (98.9% … method for early classification diagnosis for breast cancer. …

… hybrid method has shown the performance classification … the performance of breast cancer
classification in terms of … benign tumors using machine learning techniques based on Bagging…

… based cancer classification. In our study we evaluate popular machine learning methods (SVM,
Naive Bayes, Nearest Neighbor, C4.5 and RIPPER) for classifying cancers based on …

… suggestive cures depend on the classification plans or patterns. … multi machine learning
techniques for the classification of malignant and benign tumors for the Wisconsin breast cancer …

… ensemble machine learning … machine learning techniques in cancer classification, namely
C4.5 decision tree, and bagged and boosted decision trees. We have performed classification …