We have used two different datasets for the implementation
- Income-Classification: https://www.kaggle.com/lodetomasi1995/income-classification
- human activity recognition with smartphones: https://www.kaggle.com/uciml/human-activity-recognition-with-smartphones
- The implementation was done using Pipeline, ColumnTransformer and OneHotEncoder to fit.
- Different algorithms with parameter tuning (RandomizedSearchCVand GridSearchCV) and cross-validation to classify the "price".
- Logistic Regression
- Support Vector Machines
- Naïve Bayes
- K-Nearest Neighbors
- Logistic Regression
- OneVsRestClassifier with LogisticRegression
- Support Vector Machines
- OneVsOneClassifier with Support Vector Machines
- Naive Bayes
- KNN