| 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
| .
| .
| .
| |