Regression Node Catalog
Regression category
Generated from 5 catalog nodes in AI/ML/Regression.
Nodes in this category
Showing 5 of 5 generated node docs.
Train Regression (Linear)
AI/ML/RegressionFit/Train Linear Regression Model
Train Regressor (GLM / Tweedie)
AI/ML/RegressionFit/Train a Generalized Linear Model. Pick the distribution that matches the target: Normal for unbounded values, Poisson for counts, Gamma for positive skewed amounts, Inverse Gaussian for heavy tails.
Train Regressor (K-Nearest Neighbours)
AI/ML/RegressionFit a K-Nearest-Neighbours regressor that averages the target of the nearest training rows. Non-parametric and instance based: the fitted model embeds a verbatim copy of the whole training set instead of learned coefficients, so every training row (and any personal data in it) travels with the model, is written into every saved model file and can be reconstructed by anyone holding it. Treat the model with the same care as the source table.
Train Regressor (Ridge/Lasso/ElasticNet)
AI/ML/RegressionFit/Train a penalized linear regression model. Ridge shrinks all coefficients, Lasso drives irrelevant ones to exactly zero (feature selection), Elastic Net mixes both.
Train Regressor (SVM)
AI/ML/RegressionFit/Train a Support Vector Regressor. Learns non-linear targets through a kernel, with epsilon-SVR or nu-SVR.