| Technique | Description | ScalaTion Class | Status |
| Simple Linear Regression | Fit parameters b0 and b1 in y = b0 + b1 x | SimpleRegression | implemented |
| Multiple Linear Regression | Fit parameter vector b in y = b dot x | Regression | implemented |
| Polynomial Regression | Fit parameter vector b in y = b dot x where x is formed from powers of parameter t | PolyRegression | implemented |
| Nonlinear Regression | Fit parameter vector b in y = f(b, x) when f is nonlinear in b | NonLinRegression | implemented |
| Perceptron | Adjust weights so the output scalar y is predicted from the input vector x | Perceptron | implemented |
| Neural Networks | Adjust weights so the output vector y is predicted from the input vector x | NeuralNet | under development |
| Radial Basis Functions | . | . | . |
| ARMA Time Series Analysis | Auto-Regressive, Moving-Average models | ARMA | under development |
| ARIMA Time Series Analysis | . | . | . |
| Principal Component Analysis | Project a data matrix along its main eigenvectors to reduce dimensionality | PrincipalComponents | implemented |
| Factor Analysis | Analyze a data matrix in terms of given set of factors. | FactorAnalysis | started |
| Canonical Correlation Analysis | Analyze/maximize the correlation between two data matrices. | CanCorrelation | started |
| Technique | Description | ScalaTion Class | Status |
| kNN Classifier | Classify based on k Nearest Neighbors | KNN_Classifier | implemented |
| Naive Bayes Integer Classifier | Classify integer data based on product of conditional probabilities P(X_i | C) | NaiveBayesInt | implemented |
| Naive Bayes Classifier | Classify real data based on product of conditional probabilities P(X_i | C) | NaiveBayes | implemented |
| Bayesian Network | Classify data based on product of conditional probabilities P(X_i | C, {X_j}) | BayesNetwork | under development |
| ID3 Decision Trees | Classify data using simple decision trees | DecisionTreeID3 | implemented |
| C45 Decision Trees | Classify data using decision trees that handle continuous values | DecisionTreeC45 | implemented |
| Support Vector Machines | Classify data by finding optimal separating hyperplane | SupportVectorMachine | implemented |
| Logistic Regression | Used when the dependent variable y is binary | LogisticRegression | implemented |
| CART | Classification And Regression Trees | . | . |
| Technique | Description | ScalaTion Class | Status |
| K-Means Clustering | Cluster the data into k clusters | KMeansClustering | implemented |
| Hierachical Clustering | Cluster the data into hierachical groups | HierClustering | implemented |
| Markov Clustering | Cluster the nodes in a graph | MarkovClustering | implemented |
| Mixture Model | . | . | . |