Dataset: Breast Cancer

About this Dataset

Breast Cancer

Description:
Breast cancer is the most prevalent cancer among women globally, accounting for 25% of all cancer cases. In 2015 alone, it impacted over 2.1 million individuals. The disease begins when cells in the breast grow uncontrollably, forming tumors that can be detected via X-ray or felt as lumps.

The primary challenge in its detection is classifying tumors as malignant (cancerous) or benign (non-cancerous). We invite you to analyze and classify these tumors using machine learning techniques, specifically Support Vector Machines (SVMs), with the Breast Cancer Wisconsin (Diagnostic) Dataset.

Acknowledgements:
This dataset is sourced from Kaggle.

Objective:

Understand and clean the dataset if necessary.
Build classification models to predict if the cancer is malignant or benign.
Fine-tune hyperparameters and compare the performance of various classification algorithms.

Tables

Breast Cancer

@kaggle.rahmasleam_breast_cancer.breast_cancer

148.22 KB
569 rows
32 columns


CREATE TABLE breast_cancer (
  "id" BIGINT,
  "diagnosis" VARCHAR,
  "radius_mean" DOUBLE,
  "texture_mean" DOUBLE,
  "perimeter_mean" DOUBLE,
  "area_mean" DOUBLE,
  "smoothness_mean" DOUBLE,
  "compactness_mean" DOUBLE,
  "concavity_mean" DOUBLE,
  "concave_points_mean" DOUBLE,
  "symmetry_mean" DOUBLE,
  "fractal_dimension_mean" DOUBLE,
  "radius_se" DOUBLE,
  "texture_se" DOUBLE,
  "perimeter_se" DOUBLE,
  "area_se" DOUBLE,
  "smoothness_se" DOUBLE,
  "compactness_se" DOUBLE,
  "concavity_se" DOUBLE,
  "concave_points_se" DOUBLE,
  "symmetry_se" DOUBLE,
  "fractal_dimension_se" DOUBLE,
  "radius_worst" DOUBLE,
  "texture_worst" DOUBLE,
  "perimeter_worst" DOUBLE,
  "area_worst" DOUBLE,
  "smoothness_worst" DOUBLE,
  "compactness_worst" DOUBLE,
  "concavity_worst" DOUBLE,
  "concave_points_worst" DOUBLE,
  "symmetry_worst" DOUBLE,
  "fractal_dimension_worst" DOUBLE
);