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
  • K-Means
    • Lloyd’s method
    • Usage example
    • API
      • Methods
      • Descriptor
      • Model
      • Training onedal::train(...)
        • Input
        • Result
        • Operation semantics
      • Inference onedal::infer(...)
        • Input
        • Result
        • Operation semantics
• Nearest Neighbors (kNN)
  • k-Nearest Neighbors Classification (k-NN)
    • Mathematical formulation
      • Training
        • Training method: brute-force
        • Training method: k-d tree
      • Inference
        • Inference method: brute-force
        • Inference method: k-d tree
    • Programming Interface
      • Descriptor
      • Computational methods
      • Model
      • Training train(...)
        • Input
        • Result
        • Operation
      • Inference infer(...)
        • Input
        • Result
        • Operation
• Decomposition
  • Principal Components Analysis (PCA)
    • Covariance-based method
    • SVD-based method
    • Sign-flip technique
    • Usage example
    • API
      • Methods
      • Descriptor
      • Model
      • Training onedal::train(...)
        • Input
        • Result
        • Operation semantics
      • Inference onedal::infer(...)
        • Input
        • Result
        • Operation semantics