Sentence examples for between two classes using from inspiring English sources
This paper presents an ontology-based approach that can determine the similarity between two classes using feature-based similarity measures that replace features with attributes.
First, the genes were ranked according to the differential expression between two classes using only the pilot study data and the top 3000 genes in this ranking were selected (Wilcoxon rank sum test).
In this study, these 50 cell lines are divided into two classes based on the status of p53 (wild type vs mutant), and GIENA and GSA methods are applied to detect pathways enriched in differential interactions and genes between two classes using the mRNA expression data.
The models incorporated genes that were differentially expressed between the two classes using a two-sample t-test.
The random-variance t-test was applied to identify genes differentially expressed between the two classes using Biometric Research Branch BRBB) ArrayTools (National Cancer Institute, Bethesda, MD; Simon et al, 2007).
To address such limitations, hybrid translational models have more recently been developed to bridge the gaps between these two classes, using established knowledge of molecular cell biology to link pharmacodynamic responses to cell proliferation and survival.
We explored models with two to seven classes using all measures, and systematically eliminated variables and levels of variables that did not distinguish between classes, tested categorical variables derived from count measures, and combined variables that were highly collinear.
Then features that were significantly differentially expressed between two classes were identified using an F-test (significance level 0.05) to check for equal variances in each class for every exon or gene.
Unlike the traditional clustering methods, such as k-mean, which finds the most featured representatives of a class, the strategy of the GSVM-RU method used in this study is to find the samples close to the border between two classes, which are used to draw the separating hyperplane.
Note that in all the cases, BPH and Stroma classes present the highest error rate in terms of classification due to the similarities between two classes; however the use of SSGLDM with (S = 3 bands) reduces significantly the error rate in these classes.
The points (n = 4,000) were sampled using stratification between two classes (yellow, intertidal; purple, other) within the mapped area of our analysis.
