Predicting Breast Cancer Using Apache Spark Machine Learning Logistic Regression

Let's go through an example of Cancer Tissue Observations: Logistic regression is a popular method to predict a binary response. It is a special case of Generalized Linear models that predicts the probability of the outcome. Logistic regression measures the relationship between the Y "Label" and the X "Features" by estimating probabilities using a logistic function. The model predicts a probability which is used to predict the label class. Our data is from the Wisconsin Diagnostic Breast Cancer (WDBC) Data Set which categorizes breast tumor cases as either benign or malignant based on 9 features to predict the diagnosis.