View source: R/MCLinearDiscriminantClassifier.R
MCLinearDiscriminantClassifier | R Documentation |
A linear discriminant classifier that updates the estimates of the means and covariance matrix based on unlabeled examples.
MCLinearDiscriminantClassifier(X, y, X_u, method = "invariant",
prior = NULL, x_center = TRUE, scale = FALSE)
X |
matrix; Design matrix for labeled data |
y |
factor or integer vector; Label vector |
X_u |
matrix; Design matrix for unlabeled data |
method |
character; One of c("invariant","closedform") |
prior |
Matrix (k by 1); Class prior probabilities. If NULL, estimated from data |
x_center |
logical; Should the features be centered? |
scale |
logical; Should the features be normalized? (default: FALSE) |
This method uses the parameter updates of the estimated means and covariance proposed in (Loog 2014). Using the method="invariant" option, uses the scale invariant parameter update proposed in (Loog 2014), while method="closedform" using the non-scale invariant version from (Loog 2012).
Loog, M., 2012. Semi-supervised linear discriminant analysis using moment constraints. Partially Supervised Learning, LNCS, 7081, pp.32-41.
Loog, M., 2014. Semi-supervised linear discriminant analysis through moment-constraint parameter estimation. Pattern Recognition Letters, 37, pp.24-31.
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EMLinearDiscriminantClassifier
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GRFClassifier
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ICLeastSquaresClassifier
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ICLinearDiscriminantClassifier
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KernelLeastSquaresClassifier
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LaplacianKernelLeastSquaresClassifier()
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LaplacianSVM
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LeastSquaresClassifier
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LinearDiscriminantClassifier
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LinearSVM
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LinearTSVM()
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LogisticLossClassifier
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LogisticRegression
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MCNearestMeanClassifier
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MCPLDA
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MajorityClassClassifier
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NearestMeanClassifier
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QuadraticDiscriminantClassifier
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S4VM
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SVM
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SelfLearning
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TSVM
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USMLeastSquaresClassifier
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WellSVM
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svmlin()
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