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