A_optimal_cat: Get the most informative subjects from unlabeled dataset for...

Description Usage Arguments Details Value

View source: R/RcppExports.R


Get the most informative subjects from unlabeled dataset under the categorical case.


A_optimal_cat(X, beta, W, unlabeledIDs)



A matrix containing all the samples except their labels including the labeled samples and the unlabeled samples.


A matrix contains the estimated coefficient. Note that the beta is a n * k matrix which n is the number of the explanatory variables and k+1 is the number of categories


A matrix denotes the inverse information matrix of the coefficient beta.


A numeric vector for the unique identification of the unlabeled. dataset.


A_optimal_cat uses the A optimality criterion from the experimental design to choose the most informative subjects under the the categorical case. We have obtained the variance-covariance matrix based on the current labeled samples which indicates how much information there is. Then we should repeatly calculate the information matrix after we choose a sample from the unlabeled dataset. Once we finish the iteration, we pick the sample which has the most information.


a index of the most informative subjects from unlabeled dataset for the categorical case

seqest documentation built on July 2, 2020, 2:28 a.m.

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