A DISCRIMINANT FUNCTION FOR PLANT SELECTION

Selecting parental materials for hybridization by discriminant function

A simple discriminant function for hepatic disease.

Tests of hepatic function do not correlate highly and this, together with their skew distribution, makes the information provided by them difficult to interpret. By means of an appropriate transformation it is possible to normalise their distributions so that the information from them can be combined in the form of a discriminant function which is not only easy to interpret but gives an index o...

A Trivial Linear Discriminant Function

In this paper, we focus on the new model selection procedure of the discriminant analysis. Combining resampling technique with k-fold cross validation, we develop a k-fold cross validation for small sample method. By this breakthrough, we obtain the mean error rate in the validation samples (M2) and the 95% confidence interval (CI) of discriminant coefficient. Moreover, we propose the model sel...

Discriminant Feature Selection for Texture Classification

The computational complexity of a texture classification algorithm is limited by the dimensionality of the feature space. Although finding the optimal feature subset is a NP-hard problem [1], a feature selection algorithm that can reduce the dimensionality of problem is often desirable. In this paper, we report work on a feature selection algorithm for texture classification using two subband f...

Discriminant Analysis for Unsupervised Feature Selection

Feature selection has been proven to be efficient in preparing high dimensional data for data mining and machine learning. As most data is unlabeled, unsupervised feature selection has attracted more and more attention in recent years. Discriminant analysis has been proven to be a powerful technique to select discriminative features for supervised feature selection. To apply discriminant analys...