Memory Models¶
In-memory estimators for fast, local experimentation. Train on a sampled or materialized VastFrame, iterate quickly, then promote the winning model to in-database inference with the VAST Models API.
Clustering algorithms that group data points and reveal the inherent patterns within your datasets.
Decomposition techniques that break down complex data structures, enhancing understanding and simplifying analysis.
Ensemble methods that combine multiple models to achieve superior predictive accuracy.
Linear models for straightforward representations, ideal for scenarios where simplicity is key.
Naive Bayes algorithms for efficient, rapid classification — especially useful on large datasets.
Streamline data preparation to ensure optimal input for your machine learning models.
Decision trees for robust, interpretable models.