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BreastCancerPrediction

Different ML algorithms applied to Breast Cancer dataset to predict whether a tumor is benign or malignant

Dataset Information:

The dataset consists of the following fields.

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)

There are 699 instances and each containing information on 9 features of the tumor. The last field is the Class field specifying which class the tumor belongs to.

Approach

The approaches implemented are -

  1. a. Instance Selection
    b. Classificatisn using fuzzy rough nearest neighbour classifier

  2. a. K-means + C4.5 decision tree classifier

  3. a. Feature Selection using Decision Trees
    b. Reduction of features using PCA
    c. NN Classifier