VAST Models¶
Hybrid ML workflow: train with sklearn / Spark, deploy for in-database inference at scale. Every estimator below runs natively against your VAST relation — no extraction, no copies, no leaving the database.
Classification
Logistic Regression, Random Forest, GradientBoosting, Naive Bayes
Regression
Linear, Ridge, Lasso, Random Forest, GradientBoosting
Time Series
ARIMA, VAR, Moving Average, Seasonal Decomposition
Clustering & Anomalies
K-Means, DBSCAN, Isolation Forest, Local Outlier Factor
Preprocessing
PCA, Normalization, One-Hot Encoding, Feature Scaling
Text Analytics
TF-IDF, Word Embeddings, Sentiment Analysis
Pipeline (Beta)
Chain preprocessing, training, and inference steps