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

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Deep LearningBreast-Cancer-Wisconsin--Original--Classification
Overview

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:

  1. Sample code number: id number
  2. Clump Thickness: 1 - 10
  3. Uniformity of Cell Size: 1 - 10
  4. Uniformity of Cell Shape: 1 - 10
  5. Marginal Adhesion: 1 - 10
  6. Single Epithelial Cell Size: 1 - 10
  7. Bare Nuclei: 1 - 10
  8. Bland Chromatin: 1 - 10
  9. Normal Nucleoli: 1 - 10
  10. Mitoses: 1 - 10
  11. Class: (2 for benign, 4 for malignant)
Owner
Astitva Veer Garg
CSE Undergraduate W/S Artificial Intelligence and Machine Learning From SRM Institute Of Science and Technology
Astitva Veer Garg
GitHub Repository
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