Algorithms in TAP Analytics Toolkit (ATK)

The algorithms in TAP, which are both helper- and prediction-oriented, are consistently evolving and growing to address a rapidly growing set of use cases. Some of the algorithms currently available within TAP include:

Classification Algorithms

  • Logistic Regression
  • Naive Bayes
  • Random Forest
  • SVM with SGD
  • Lib SVM

Regression Algorithms

  • Linear Regression
  • Random Forest

Clustering Algorithms

  • K Means

Dimensionality Reduction Algorithms

  • Principal Component Analysis
  • Topic Modeling Algorithms
    • Latent Dirichlet Allocation (LDA)
  • Recommendation algorithms
    • Collaborative Filtering Using ALS (Alternating Least Squares)
  • Clustering Algorithms
    • Power Iteration Clustering
  • Graph Algorithms
    • Label Propagation
    • Loopy Belief Propagation
  • Time series algorithms
    • ARIMA: Auto Regressive Integrated Moving Average
    • ARX: Auto Regressive with Exogenous Variables