# Modeling Function Overview

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**High-Level Modeling Functions**
The following output a model structure (or similar) and are generally considered "high-level" modeling functions designed for relatively simple use by less-experienced users as well as expert users.

- analysis - Graphical user interface for data analysis.
- caltransfer - Create or apply calibration and instrument transfer models.
- cluster - KNN and K-means cluster analysis with dendrograms.
- cls - Classical Least Squares regression for multivariate Y.
- corrspec - Resolves correlation spectroscopy maps.
- frpcr - Full-ratio PCR calibration and prediction.
- knn - K-nearest neighbor classifier.
- lwr - Locally weighted regression for univariate Y.
- mcr - Multivariate curve resolution with constraints.
- mlr - Multiple Linear Regression for multivariate Y.
- modelselector - Create or apply a model selector model.
- mpca - Multi-way (unfold) principal components analysis.
- npls - Multilinear-PLS (N-PLS) for true multi-way regression.
- parafac - Parallel factor analysis for n-way arrays.
- parafac2 - Parallel factor analysis for unevenly sized n-way arrays.
- pca - Principal components analysis.
- pcr - Principal components regression for multivariate Y.
- pls - Partial least squares regression for multivariate Y.
- plsda - Partial least squares discriminant analysis.
- purity - Self-modeling mixture analysis method based on purity of variables or spectra.
- simca - Soft Independent Method of Class Analogy.
- svm - SVM Support Vector Machine for regression.
- svmda - SVM Support Vector Machine for classification.
- tld - Trilinear decomposition.
- tucker - Analysis for n-way arrays.
- xgb - Gradient Boosted Tree Ensemble for regression using XGBoost.
- xgbda - Gradient Boosted Tree Ensemble for classification (Discriminant Analysis) using XGBoost.

**Medium-Level Modeling Functions**

The following provide functionality not generally available through another higher-level function and may be of use for certain analysis methods but also require more knowledge of Matlab and the methods involved.

- gram - Generalized rank annihilation method.
- mlpca - Maximum likelihood principal components analysis.
- coda_dw - Calculates values for the Durbin_Watson criterion of columns of data set.
- comparelcms_sim_interactive - Interactive interface for COMPARELCMS.
- cr - Continuum Regression for multivariate y.
- evolvfa - Evolving factor analysis (forward and reverse).
- ewfa - Evolving window factor analysis.
- glsw - Generalized least-squares weighting/preprocessing.
- gram - Generalized rank annihilation method.
- lwrpred - Engine for locally weighted regression models.
- mlpca - Maximum likelihood principal components analysis.
- polypls - PLS regression with polynomial inner-relation.
- ridge - Ridge regression by Hoerl-Kennard-Baldwin.
- wtfa - Window target factor analysis.

(Sub topic of Categorical_Index)