Sentence examples for many input variables from inspiring English sources

The results of the analyses are difficult to describe simply as there appears to be a non-linear relationship between some of the many input variables.

A neuro-fuzzy model was able to simulate water levels with an R2 of 0.88, performing equally in comparison to a multiple linear regression model based on twice as many input variables, some with much less lead time.

In many situations, even though the number of model runs needed for a given study is a factor of many input variables, it is independent of the number of agents.

Some of the advantages of Random Forest in a virtual screening setting are: efficient processing of large numbers of examples; capability to handle many input variables; estimate variable importance; by design immune to overfitting and problems due to missing data; and it can predict balanced class populations from unbalanced data sets.

But clinical effect sizes are only one of the many input variables needed for a HTA (others include estimates on incidence of morbidity and mortality, costs and utilities), and meta-analysis for estimating these other types of variables have been used to a far lesser extent [1].

Considering the relatively small dataset currently available for modelling DNA-binding sites, too many input variables may result in model overfitting for most machine learning algorithms.

Assuming that many influential input variables to energy models are well studied and observed, such as gross domestic product, population growth and the like, the approach should at least be discussed for those variables.

This means that in practice, many different input variables need to be assessed if large and complex models are analysed and a significant amount of data collection and preparation seems necessary.

It has been shown that RFs outperform AdaBoost ensembles on noisy datasets, and can perform well on data with many weak input variables [ 17].

The LTS criteria lacks many of the input variables found significant in predicting both route choice and mode choice, including several that are required for its more expensive alternatives.

Because the measured spectra consist of many highly correlated input variables which can lead to instable parameter estimates, a PCA [ 11] was applied as a method of dimensionality reduction.