To Design and Implement Logistic Regression to Classify Between Benign and Malignant Cancer Types

Jan 14, 2022 1 min read

Breast Cancer Wisconsin (Original) Classification

Data Set Information:

Samples arrive periodically as Dr. Wolberg reports his clinical cases. The database therefore reflects this chronological grouping of the data.

Note that the results summarized above in Past Usage refer to a dataset of size 369, while Group 1 has only 367 instances. This is because it originally contained 369 instances; 2 were removed.

Attribute Information:

Sample code number: id number
Clump Thickness: 1 – 10
Uniformity of Cell Size: 1 – 10
Uniformity of Cell Shape: 1 – 10
Marginal Adhesion: 1 – 10
Single Epithelial Cell Size: 1 – 10
Bare Nuclei: 1 – 10
Bland Chromatin: 1 – 10
Normal Nucleoli: 1 – 10
Mitoses: 1 – 10
Class: (2 for benign, 4 for malignant)

GitHub

John was the first writer to have joined pythonawesome.com. He has since then inculcated very effective writing and reviewing culture at pythonawesome which rivals have found impossible to imitate.