Sentence examples for feature partitioning from inspiring English sources

These issues are critical to the design and performance of feature partitioning approaches to PCA computation.

We show several open issues and present a novel algorithm, SubXPCA which proposes a solution to the cross-sub-pattern correlation issue in the feature partitioning framework.

In this paper we propose a general feature partitioning framework to PCA computation and raise issues of cross-sub-pattern correlation, feature ordering dependence, selection of sub-pattern size, overlap of sub-patterns and selection of principal components.

Since the accuracy of an assessment model can be largely affected by processing vague patient features, this paper also discusses a clustering-based method for patient feature partitioning.

The efficiency in using the transformed dataset to perform normal/tumor classification was investigated using feature partitioning with informative features (gene annotation) as discriminating axes (single gene expression or pair-wise gene expression ratio).

Regarding the Feature Partitioning Method (FPM), in order to discriminate between the normal/tumor tissues based on specific feature i (single gene expression), the first step is to determine the threshold value, T i, that can optimally splits all the tissue samples into tumor and normal tissue.

Epigenetic modifications and other chromatin features partition the genome on multiple length scales.

A decision tree can be treated as a set of Boolean functions of features and these conjunctions of features partition training samples into groups with homogenous class label.

The paraphyses are cylindrical in shape and feature septa partitioning the hypha into distinct cells.

We propose a decision tree-based methodology for our feature space partitioning.

The proposed embedded framework features rate partitioning and UART interface for performance validation and troubleshooting.