Models Available

Classification

• Baseline
  • Prior Dummy Classifier - Explanation of the prior dummy classifier.
  • Uniform Dummy Classifier - Overview of the uniform dummy classifier.
  • Stratified Dummy Classifier - Explanation of the stratified dummy classifier.
• Linear
  • Perceptron Classifier - Description of the perceptron algorithm.
  • Logistic Regression Classifier - Overview of logistic regression for binary classification.
  • Stochastic Gradient Descent Classifier - Explanation of the SGD classifier.
  • Passive Aggressive Classifier - Overview of the passive-aggressive algorithm.
  • Intelex Logistic Regression Classifier - Description of the Intelex variant of logistic regression.
  • Stochastic Dual Coordinate Ascent Classifier - Overview of this advanced classifier.
• Nearest Neighbour
  • Nearest Centroid Classifier - Explanation of the nearest centroid classifier.
• Gradient
  • Fast Iterative Shrinkage/Thresholding Classifier - Description of this classifier.
  • Coordinate Descent Classifier - Overview of coordinate descent methods.
  • Stochastic Averaged Gradient Ascent Classifier - Explanation of this classifier.
  • Adaptive Gradient Classifier - Overview of adaptive gradient methods.
• Tree
  • Random Forest Classifier - Description of the random forest algorithm.
  • Decision Tree Classifier - Overview of decision tree classification.
  • Extremely Randomized Tree Ensemble Classifier - Explanation of this ensemble method.
  • LightGBM Classifier - Overview of LightGBM for efficient classification.
  • CatBoost Classifier - Description of CatBoost for categorical features.
  • XGBoost Classifier - Overview of XGBoost for gradient boosting.
• Kernel
  • Linear Support Vector Machine Classifier - Explanation of linear SVM.
  • Support Vector Machine Classifier - Overview of SVM for classification.
• Ensemble
  • Random Forest Classifier - Description of random forest ensemble.
  • Extremely Randomized Tree Ensemble Classifier - Overview of this ensemble method.
  • LightGBM Classifier - Explanation of LightGBM in ensemble context.
  • CatBoost Classifier - Overview of CatBoost in ensemble context.
• Bayesian
  • Gaussian Naive Bayes Classifier - Explanation of Gaussian Naive Bayes.
  • Linear Discriminant Analysis Classifier - Overview of LDA for classification.

Regression

• Baseline
  • Mean Dummy Regressor - Explanation of the mean dummy regressor.
  • Median Dummy Regressor - Overview of the median dummy regressor.
• Linear
  • Automatic Relevance Determination Regressor - Description of this regression method.
  • Bayesian Ridge Regressor - Overview of Bayesian ridge regression.
  • Elastic Net Regressor - Explanation of elastic net regression.
  • Huber Regressor - Overview of Huber regression.
  • Lasso Regressor - Description of Lasso regression.
  • Linear Regressor - Overview of standard linear regression.
  • Passive Aggressive Regressor - Explanation of the passive-aggressive regression method.
  • Ridge Regressor - Overview of ridge regression.
  • Stochastic Gradient Descent Regressor - Description of SGD for regression.
  • Intelex Elastic Net Regressor - Overview of the Intelex variant of elastic net.
  • Intelex Linear Regressor - Description of the Intelex linear regression.
• Gradient
  • Coordinate Descent Regressor - Explanation of coordinate descent for regression.
• Tree
  • Decision Tree Regressor - Description of decision tree regression.
  • Random Forest Regressor - Overview of random forest regression.
  • LightGBM Regressor - Explanation of LightGBM for regression.
  • CatBoost Regressor - Overview of CatBoost for regression.
  • XGBoost Regressor - Description of XGBoost for regression.
• Kernel
  • Linear Support Vector Machine - Explanation of linear SVM for regression.
• Ensemble
  • Random Forest Regressor - Description of random forest for regression.
  • LightGBM Regressor - Overview of LightGBM in regression context.
  • CatBoost Regressor - Explanation of CatBoost in regression context.
  • XGBoost Regressor - Overview of XGBoost in regression context.
• Bayesian
  • Automatic Relevance Determination Regressor - Description of this method.
  • Bayesian Ridge Regressor - Overview of Bayesian ridge regression.
• NLP
  • NLP Sequence Classifier - Description of NLP sequence classification.
  • NLP Sequence Regressor - Overview of NLP sequence regression.