Sentence examples for subtle data analysis from inspiring English sources

We then use these results to discover an unexpected sensitivity of validation to subtle data analysis decisions.

An important and subtle shortcoming of some data analysis protocols is to not balance the training and testing data, seriously affecting variance, statistical power (and potentially biasing error estimates).

Unlike the traditional feature selection methods, it suppresses redundant global features and extracts local features to capture gross and subtle data characteristics via multi-resolution data analysis.

Furthermore, our proposed derivative component analysis suggests the subtle data characteristics gleaning and de-noising are essential in separating true signals from red herrings for high-dimensional proteomic profiles, which can be more important than the conventional feature selection or dimension reduction.

Secondly, 450 k data analysis was sensitive to subtle methylation changes at differentially methylated regions to the point where it detected variations that were undetected in targeted testing.

Furthermore, we found that semi-quantitative data analysis could capture the subtle proteome changes occurring upon microbial stimulation that differentiate resting, from lipopolysaccharides or M. tuberculosis stimulated monocytic samples.

As a same-dimensional but a low variance approximation for the original data by keeping the most important global data characteristics and capturing local data characteristics, the meta-profile X* makes the following independent component analysis more sensitive in catching subtle data behavior than applying ICA directly applying to the original data.

Considering these subtle changes in gene expression, we performed additional microarray data analysis to increase the probability of finding biologically significant targets.

The data analysis shows that the students were in their "regime of competence" for grasping subtle nuances of the materials and for providing important hints for revising them.

Delimitation is subtle enough to be difficult to determine by eye and requires investigation of large populations using multivariate data analysis.

The inclusion of computer assisted data analysis such as machine-learning derived support vector machine analyses may allow for detecting subtle changes, which are not reliably detected by visual inspection [ 30, 31].