4.3 Choose the Algorithm

Learn about providing the algorithm settings for a model.

The ALGO_NAME setting specifies the algorithm for a model. If you use the default algorithm for the machine learning technique, or if there is only one algorithm available for the machine learning technique, then you do not need to specify the ALGO_NAME setting.

Table 4-72 Oracle Machine Learning Algorithms

ALGO_NAME Value	Algorithm	Default?	Machine Learning Model Function
ALGO_AI_MDL	Minimum Description Length	—	Attribute importance
ALGO_APRIORI_ASSOCIATION_RULES	Apriori	—	Association
ALGO_CUR_DECOMPOSITION	CUR Matrix Decomposition	—	Attribute importance
ALGO_DECISION_TREE	Decision Tree	—	Classification
ALGO_EXPECTATION_MAXIMIZATION	Expectation Maximization	—	Clustering
ALGO_EXPLICIT_SEMANTIC_ANALYS	Explicit Semantic Analysis	—	Feature extraction and classification
ALGO_EXPONENTIAL_SMOOTHING	Exponential Smoothing	—	Time series
ALGO_EXTENSIBLE_LANG	Language used for an extensible algorithm	—	All machine learning functions are supported
ALGO_GENERALIZED_LINEAR_MODEL	Generalized Linear Model	—	Classification and regression
ALGO_KMEANS	k-Means	yes	Clustering
ALGO_MSET_SPRT	Multivariate State Estimation Technique - Sequential Probability Ratio Test	—	Anomaly detection (classification with no target)
ALGO_NAIVE_BAYES	Naive Bayes	yes	Classification
ALGO_NEURAL_NETWORK	Neural Network	—	Classification
ALGO_NONNEGATIVE_MATRIX_FACTOR	Non-Negative Matrix Factorization	yes	Feature extraction
ALGO_O_CLUSTER	O-Cluster	—	Clustering
ALGO_RANDOM_FOREST	Random Forest	—	Classification
ALGO_SINGULAR_VALUE_DECOMP	Singular Value Decomposition (can also be used for Principal Component Analysis)	—	Feature extraction
ALGO_SUPPORT_VECTOR_MACHINES	Support Vector Machine	yes	Default regression algorithm; regression, classification, and anomaly detection (classification with no target)
ALGO_XGBOOST	XGBoost	—	Classification and regression