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Algorithms

The Algorithms component consists of classes that implement algorithms for data analysis (data mining) and data modeling (training and prediction). These algorithms include matrix decompositions, clustering, classification, and regression algorithms, as well as association rules discovery.

• Clustering
  • DBSCAN
  • K-Means
  • K-Means initialization
• Covariance
  • Covariance
• Decomposition
  • Principal Components Analysis (PCA)
• Ensembles
  • Decision Forest Classification and Regression (DF)
• Graph
  • Subgraph Isomorphism
  • Connected Components
• Kernel Functions
  • Linear kernel
  • Polynomial kernel
  • Radial Basis Function (RBF) kernel
  • Sigmoid kernel
• Nearest Neighbors (kNN)
  • k-Nearest Neighbors Classification and Search (k-NN)
• Pairwise Distances
  • Minkowski distance
  • Chebyshev distance
  • Cosine distance
• Statistics
  • Basic Statistics
• Support Vector Machines
  • Support Vector Machine Classifier and Regression (SVM)

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Homogeneous table

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Clustering