|A basic algorithm predicting quantitative outcomes based on independent variables.
|It’s used for binary classification problems, predicting a probability between 0 and 1.
|K-Nearest Neighbours (KNN)
|A multi-use algorithm that can perform both classification and regression.
|Support Vector Machine (SVM)
|An algorithm used typically for binary classification problems.
|An algorithm used for solving both regression and classification problems.
|It uses ensemble learning method for classification, regression and other tasks.
|Based on Bayes’ Theorem, this algorithm is particularly suited when the dimensionality of the inputs is high.
|An iterative algorithm that divides a group of n datasets into k subgroups/clusters.
|Gradient Boosting Algorithms (GBM)
|A machine learning technique for regression and classification problems.
|Principal Component Analysis (PCA)
|A technique used to emphasize variation and bring out strong patterns in a dataset.
|Artificial Neural Networks (ANN)
|A computing system inspired by the biological neural networks that constitute animal brains.
|A class of machine learning algorithms that use artificial neural networks with multiple layers.
|Time Series Algorithms
|A family of algorithms designed specifically for use in time series data.
|A method of clustering where you build nested clusters by merging or splitting them successively.
|Association Rule Learning
|A rule-based machine learning method for discovering relationships between variables in large databases.
|A technique for analyzing multiple regression data that suffer from multicollinearity.
|A regression analysis method that performs both variable selection and regularization.
|A regularized regression method that linearly combines the L1 and L2 penalties of the lasso and ridge methods.
|A statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables.
|It is used when the dependent variable is categorical and the independent variable is interval in nature.