Sentence examples for prior data set from inspiring English sources

PCA is an unsupervised pattern recognition method without prior data set information.

Comparisons of pERK/ERK and pAkt/Akt vs cavin-3 level in this data set together with that of the prior data set using SV589 fibroblasts expressing endogenous levels of cavin-3 show that pERK/ERK and pAkt/Akt levels correlate with the level of cavin-3, but not the levels of cavin-1 or caveolin-1.

Finally, the current year data included additive Gaussian noise, whereas the prior data sets did not.

Atwell et al. [12] genotyped 107 lines of Arabidopsis with the 250K array to determine which SNPs were polymorphic between two given lines to a high degree of confidence, using quality ensuring measures such as multiple prior data sets for sequence confirmation, the filtering of bad arrays and bad SNPs using mismatch rates, and removing non-binary SNPs.

Each simulated data set consists of study data and 3 years of prior data, which is the number of prior data sets used in the Glasgow motivating study.

The majority of the data-set (21 of 33) were obtained from a previous collation [1]: networks were only omitted from that prior data-set if neither Cws or CΔ were available for them (and hence were of no practical use to us here).

Many of the additional networks we added filled sub-domains missing from the prior data-set, for example: the dolphin network [41] is an example of an animal social network; the cortical area connectivity map [42] is an example of large-scale neural connectivity.

However, the marker registration is associated with high logistics, since the markers have to be placed prior to data set acquisition and have to be kept in their position until the patient enters the operating room.

In the case of a prior twin study, the posterior resulting from that prior study with data set x is proportional to the likelihood function.

Prior estimate of data set modelability can reduce modelers efforts by focusing in the most promising problems or identifying the challenging ones that may require more data, more descriptor variability or different strategies.

Conditioning this prior to the design data set is done by Kalman smoothing.