❤ Building a Simple Machine Learning Model on Breast Cancer Data || Still working on the deployment phase. This project is a part of EDA (Exploratory Data Analysis) where the main characteristics are analysed followed by a visualization.
✔Tasks performed in this model :
- Import essential libraries
- Load breast cancer dataset and explore
- Creating Dataframes
- Data Visualization
- Pairplot
- Counterplot
- Heatmap
- heatmap of breast cancer data frame
- heatmap of correlation matrix
- Correlation bar plot
- Data Processing
- Split data frame in train and test
- Feature Scaling
- Breast Cancer Deetction ML model
- Support Vector Classifier
- Logistic Regression
- K-nearest neighbor Classifier
- Naive Bayes Classifier
- Decision tree Classifier
- Random Forest Classifier
- Adaboost Classifier
- XGboost Classifier
- XGboost Parameter tuning Randomized search
- Confusion matrix
- Classification report of model
- Cross Validation of model
- Saving the model
https://www.sciencedirect.com/science/article/pii/S1877050918309323