The purpose of this tutorial is to familiarize you with quickly combining components from the CNTK python library to perform a classification task. You may skip Introduction section, if you have already completed the Logistic Regression tutorial or are familiar with machine learning.
IntroductionProblem
A cancer hospital has provided data and wants us to determine if a patient has a fatal malignant cancer vs. a benign growth. This is known as a classification problem. To help classify each patient, we are given their age and the size of the tumor. Intuitively, one can imagine that younger patients and/or patient with small tumor size are less likely to have malignant cancer. The data set simulates this application where the each observation is a patient represented as a dot where red color indicates malignant and blue indicates a benign disease. Note: This is a toy example for learning, in real life there are large number of features from different tests/examination sources and doctors'experience that play into the diagnosis/treatment decision for a patient.
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