Best way to detect breast cancer by using machine learning algorithms

Abstract EN

Breast cancer is the second deadliest disease infected women worldwide.

For this reason the early detection is one of the most essential stop to overcomeit dependingon automatic devices like artificial intelligent.

Medical applications of machine learning algorithmsare mostly based on their ability to handle classification problems, including classifications of illnesses or to estimate prognosis.

Before machine learningis applied for diagnosis, it must be trained first.

The research methodology which isdetermines differentofmachine learning algorithms,such as Random tree, ID3, CART, SMO, C4.5 and Naive Bayesto finds the best training algorithm result.

The contribution of this research is test the data set with missing value and without missing value, where the missing value is one attribute is missing from one sample for data set.

The test result is show SMO is the best algorithm, especiallywhen the research removes the samples that contained the missing value.