Sentence examples for more complex analytic from inspiring English sources

One key concern with the use of more complex analytic approaches is the potential for overfitting the data as well as the lack of interpretability, especially with nonlinear approaches.

Risk prediction models are statistical algorithms, which can be simple genetic risk scores (e.g., risk allele counts), or be based on regression analyses (e.g., weighted risk scores or predicted risks) or on more complex analytic approaches such as support vector machine learning or classification trees.

Risk prediction models are statistical algorithms, which may be simple genetic risk scores (eg, risk allele counts), may be based on regression analyses (eg, weighted risk scores or predicted risks), or may be based on more complex analytic approaches such as support vector machine learning or classification trees.

Charging for more complex analytics tools is another option.

Three approaches were compared: a basic keyword search, an index search using common work terms identified by a manual review, and a more complex content analytic text mining approach.

A key issue for estimation with the more complex factor analytic models is that working variates require formation of A, in addition to A -1 as, (7) This requirement potentially reduces the efficiency of the methodology over simple pedigree models, which only require formation of A-1.

The current analytics offerings that accompany its surveys have been sufficient but have been without support for more complex analysis.

Depending on how elaborate a model one wishes to obtain, one can use b t) to yield more complex or less complex analytic solutions for the function m(t).

If a cluster-randomized design or multiple groups have been involved, the analysis will necessarily be more complex and require advanced analytic techniques.

For larger samples and/or more complex models, for which analytic likelihood calculations become intractable, the bSFS could form the basis for alternative inference methods.

As business grows faster-paced and more complex, data-mining and analytics become increasingly valuable.