Sentence examples for between a feature and from inspiring English sources

Chi square measures the dependence between a feature and a class.

Given a codebook, instead of creating a vector of frequencies, the VLAD model creates a vector of differences, as distances, between a feature and the cluster's centre.

Fleuret proposed the Conditional Mutual Information Maximization CMIMM) criterion [30], which examines the information between a feature and the class label, conditioned on each current feature.

The algorithm cycles through each class in the problem, and accounts for the redundancy between a feature and the currently built feature set, using the syntactic structure of the feature.

The latter was controlled by standard filtering using Pearson correlation as an association measure between a feature and the target.

Fleuret used the Conditional Mutual Information Maximization (CMIM) to select feature [ 18], which examines the information between a feature and the target, conditioned on each current feature.

Usually, mutual information is used as the measurement between a feature word and a class, and if the feature word belongs to the class, they have the largest amounts of mutual information.

In large-scale HTS gene expression profiling, differentially expressed genes are biologically assumed to be a small portion of the population and the correlation values between a feature variable and a class variable are exponentially distributed.

High-throughput gene expression profiling returns only a relatively small number of differentially expressed genes, and the correlation values between a feature variable and a class variable are exponentially distributed.

Feature class relevance: It is defined as the degree of feature class mutual information between a feature f and a class label C. Feature-feature relevance: It is defined as the degree of feature-feature mutual information between any two features, say (f_i) and (f_j) where (f_i, f_j in F).

The parameter p is a weight between 0 and 1. Function mfr(X i ) indicates the correlation measure between a feature subset and the target variable.