Available Algorithms

Print available algorithms for supervised learning, clustering, and decomposition.

Usage

available_supervised()

available_clustering()

available_decomposition()

Value

Called for its side effect of printing available algorithms.

Author

EDG

Examples

available_supervised()
#>           CART: Classification and Regression Trees
#>            GAM: Generalized Additive Model
#>            GLM: Generalized Linear Model
#>         GLMNET: Elastic Net
#>       Isotonic: Isotonic Regression
#>      LightCART: Decision Tree
#>       LightGBM: Gradient Boosting
#>        LightRF: LightGBM Random Forest
#>   LightRuleFit: LightGBM RuleFit
#>         Ranger: Random Forest
#>      LinearSVM: Support Vector Machine with Linear Kernel
#>      RadialSVM: Support Vector Machine with Radial Kernel
#>         TabNet: Attentive Interpretable Tabular Learning
available_clustering()
#>      CMeans: Fuzzy C-means Clustering
#>      DBSCAN: Density-based spatial clustering of applications with noise
#>      HardCL: Hard Competitive Learning
#>      KMeans: K-Means Clustering
#>   NeuralGas: Neural Gas Clustering
available_decomposition()
#>      ICA: Independent Component Analysis
#>   Isomap: Isomap
#>      NMF: Non-negative Matrix Factorization
#>      PCA: Principal Component Analysis
#>     tSNE: t-distributed Stochastic Neighbor Embedding
#>     UMAP: Uniform Manifold Approximation and Projection