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Binary classification and Multiclass classification with pipelining and parameter tuning with GridsearchCV and RandomizedSearchCV

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Binary Classification and Multi-Class Classification

Details about Dataset

We have used two different datasets for the implementation

  1. Income-Classification: https://www.kaggle.com/lodetomasi1995/income-classification
  2. 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".

Algorithms for Binary classification

  1. Logistic Regression
  2. Support Vector Machines
  3. Naïve Bayes
  4. K-Nearest Neighbors

Algorithms for multi-class classification

  1. Logistic Regression
  2. OneVsRestClassifier with LogisticRegression
  3. Support Vector Machines
  4. OneVsOneClassifier with Support Vector Machines
  5. Naive Bayes
  6. KNN

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Binary classification and Multiclass classification with pipelining and parameter tuning with GridsearchCV and RandomizedSearchCV

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