This project is about building a binary classification model, where you will be given below details (Features),
radius_mean
texture_mean
perimeter_mean
area_mean
smoothness_mean
compactness_mean
concavity_mean
concave points_mean
symmetry_mean
fractal_dimension_mean
radius_se
texture_se
perimeter_se
area_se
smoothness_se
compactness_se
concavity_se
concave points_se
symmetry_se
fractal_dimension_se
radius_worst
texture_worst
perimeter_worst
area_worst
smoothness_worst
compactness_worst
concavity_worst
concave points_worst
symmetry_worst
fractal_dimension_worst
Based on the past breast cancer data, build a machine learning binary classification model to predict if the person is Malignant (M) or Benign (B) Cancer.
Evaluation will be done based on below details,
1. Document the hypothesis
2. Loading the data
3. Understanding the data
4. Preprocessing with Exploratory Data Analysis (EDA)
5. Missing value and outlier treatment (if any)
6. Feature Engineering
7. Model Building - Build multiple models and select the best one.
S.No. |
Description |
Code File |
Solution File |