Get the most informative subjects from unlabeled dataset under the ordinal case
A_optimal_ord(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 index of the most informative subjects from unlabeled dataset for the ordinal case
A_optimal_ord uses the A optimality criterion from the experimental design to choose the most informative subjects under the the ordinal 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.