Soft Independent Modeling of Class Analogy (SIMCA) 1.0

Date Added: July 04, 2013 | Visits: 435

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Model for Soft Independent Modeling of Class Analogy (SIMCA) simca_model=simca(x,classes) input: x (samples x descriptors) for calibration classes (samples x 1) classes numbers (must be >0) output: simca_model struct with: models (1 x No. classes) struct with: (one for each class) x (samples x descriptors) input for this class clas (samples x 1) numbers for this class S (samples x pc) scores for this model L (descriptors x pc) loadings for this model ev (pc x 1) eigenvalues for this model T2 (samples x 1) Tdldc for samples of this model Q2 (samples x 1) Qdldc for samples of this model T2lim (1 x 1) Tdldc limit for this model Q2lim (1 x 1) Qdldc limit for this model stats (1 x 1) struct with: classes (No. classes x 1) class types T2 (samples x 1) Tdldc for calibration samples Q2 (samples x 1) Qdldc for calibration samples class_c (samples x 1) Predicted classes for calibration samples RMSEP (1 x 1) Root Mean Square Error for Calibration R2 (1 x 1) Correlation Coefficient for calibration suc (1 x 1) Success (%) of classification for calibration samples-------------------------------------------------------------------------- Classes prediction using SIMCA model simca_pred = simcapred(x,model,classes) input: x (samples x descriptors) new samples for prediction model (struct) with SIMCA calibration parameters classes (samples x 1) classes numbers (must be >0) (optional for model test) output: simca_pred struct with: class_p (samples x 1) predicted classes for new samples T2 (samples x 1) Tdldc for new samples Q2 (samples x 1) Qdldc for new samples RMSEP (1 x 1) Root Mean Square Error for Prediction (only if 'classes' is supplied) R2 (1 x 1) Correlation Coefficient for Prediction (only if 'classes' is supplied) suc (1 x 1) Success (%) of classification for new samples (only if 'classes' is supplied)

Requirements: No special requirements

Platforms: Matlab

Keyword: Calibration, Class, Classification, Coefficient, Correlation, Error, Predicted, Square, Success, Types

Users rating: 0/10

License: Shareware

Size: 10 KB

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