Analyzing Large Data Sets to Find Deviation PatternsOperations, such as data processing operations, can be improved by applying clustering and statistical techniques to observed behaviors in the data processing operations.Sengupta, ArijitStronger, Brad A....
ANALYZING LARGE DATA SETS USING A COMPUTER SYSTEMA method and/or system for making determinations regarding samples from biologic sources. A computer implemented method and/or system can be used to automate parts of the analysis.Boris Fain
Introduction to statistical methods for analyzing large data sets: gene-set enrichment analysis. Science Signaling, 4(190):tr4, September 2011.Clark, N. R. & Ma'ayan, A. Introduction to statistical methods for analyzing large data sets: gene-set enrichment analysis. Science ...
Another type of analysis is the division of classes of objects (sets) into subclasses (nonintersecting subsets) of the given set. Such a form of analysis is called classification. All these and other types of analysis are used both in obtaining new knowledge and in the systematization of al...
Next, specify the name of the .xdf file you will create in your working directory (use "mortDefault" instead of "mortDefaultSmall" if you are using the large data sets): mortXdfFileName <- "mortDefaultSmall.xdf" or mortXdfFileName <- "mortDefault.xdf" ...
RevoScaleR provides a framework for fast and efficient multi-core processing of large data sets. You can visualize and model data sets with millions of records on your local machine using syntax like: myLinMod <- rxLinMod(y ~ x + z, data=myData) ...
Occasionally, computer recommendations will trigger humans to do data analysis. For example, computers can monitor changing data and notify appropriate people about anomalous changes. People can use their knowledge of the world to determine if a recommendation is a false positive or deserving of deeper...
Although Machine Learning (ML) is essential for the diagnosis of a wide range of diseases, the production of large-scale data sets and the presence of numerous non-essential and redundant features in these data sets is a significant deficiency in ML algorithms8. Furthermore, in many cases, on...
Analysis in Mixed Methods Research and Evaluation A necessary condition is trivial when either the outcome represents a very small subset of the condition as illustrated in Figure 5-2, or the outcome and conditions represent very large sets and are nearly "constants" as illustrated in Figure 5-...
It often applied to the analysis of large data sets in analytical chemistry [13], medical statistics [14], pharmaceutical engineering [15, 16]. VIP analysis method used in the analysis of clinical risk factors, which helps to understand the influence of risk factors on the severity of AEs. ...