Cluster Analysis and Classification Functions: Difference between revisions
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:[[discrimprob]] - Discriminate probabilities for continuous predicted values. | :[[discrimprob]] - Discriminate probabilities for continuous predicted values. | ||
:[[knn]] - K-nearest neighbor classifier. | :[[knn]] - K-nearest neighbor classifier. | ||
:[[lda]] - Linear Discriminant Analysis. | |||
:[[plsda]] - Partial least squares discriminant analysis. | :[[plsda]] - Partial least squares discriminant analysis. | ||
:[[plsdaroc]] - Calculate and display ROC curves for PLSDA model. | :[[plsdaroc]] - Calculate and display ROC curves for PLSDA model. | ||
:[[plsdthres]] - Bayesian threshold determination for PLS Discriminate Analysis. | :[[plsdthres]] - Bayesian threshold determination for PLS Discriminate Analysis. | ||
:[[simca]] - Soft Independent Method of Class Analogy. | :[[simca]] - Soft Independent Method of Class Analogy. | ||
:[[svmda]] - SVM Support Vector Machine for classification. | |||
(Sub topic of [[Categorical_Index|Categorical_Index]]) | (Sub topic of [[Categorical_Index|Categorical_Index]]) | ||
Latest revision as of 09:13, 8 December 2023
- class2logical - Create a PLSDA logical block from class assignments.
- cluster - KNN and K-means cluster analysis with dendrograms.
- discrimprob - Discriminate probabilities for continuous predicted values.
- knn - K-nearest neighbor classifier.
- lda - Linear Discriminant Analysis.
- plsda - Partial least squares discriminant analysis.
- plsdaroc - Calculate and display ROC curves for PLSDA model.
- plsdthres - Bayesian threshold determination for PLS Discriminate Analysis.
- simca - Soft Independent Method of Class Analogy.
- svmda - SVM Support Vector Machine for classification.
(Sub topic of Categorical_Index)