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We next used correspondence analysis to examine the relationship between the three types of specific antibody responses (total, parasite and brain) and clinical outcome.
We used correspondence analysis to rapidly visualize the associations between ChIP-seq data and gene expression.
We have used correspondence analysis to further evaluate the same data sets used in hierarchical cluster analysis.
Owing to the small sample size of this study, we have used correspondence analysis to evaluate the same data sets used in hierarchical cluster analysis.
To test this idea, we used correspondence analysis [ 45] to analyze codon usage statistics for male-biased, female-biased, and unbiased genes, using a conservative cutoff of four-fold difference for biased genes.
Furthermore, Pe'er et al. [ 17] detected correlations between the domain of life and oligopeptide compositions, while Tekaia et al. [ 18] used correspondence analysis and amino acid composition to obtain high classification performance when distinguishing eukaryotes from prokaryotes.
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Using correspondence and ascending hierarchical classification analyses, homogenous groups were identified.
An example of using correspondence data is when one has a cross-lingual, cross-domain review sentiment classification task in which we could use review-correspondences to learn a mapping between the two languages.
When using correspondence data between source and target domains the method assumes that they are statistically representative (though this assumption may not always hold in real-world scenarios).
The differences in cognitive search strategy choice between researcher-defined and participant-defined tasks and between directed search and general-purpose tasks were examined using correspondence analysis.
The scoring efficacy and accuracy of EvoGrader were tested using correspondence magnitudes (i.e., inter-rater agreement) between human and computer scores.
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