Predictive modeling (PM) of the trawl system (TS) is a complex, interdisciplinary and cognitive representation TS links. vehicle predicts its operational parameters in various conditions (transition, etching warriors, trawling, hauling other processes). It also possible to process data experiments numerical simulations on basis PM together, which not compatible with mathematical physical simula...

Citation: Koutsoukas A, St. Amand J, Mishra M and Huan J (2016) Predictive Toxicology: Modeling Chemical Induced Toxicological Response Combining Circular Fingerprints with Random Forest and Support Vector Machine. Front. Environ. Sci. 4:11. doi: 10.3389/fenvs.2016.00011 Predictive Toxicology: Modeling Chemical Induced Toxicological Response Combining Circular Fingerprints with Random Forest an...

Matrix factorization is a popular technique for engineering features for use in predictive models; it is viewed as a key part of the predictive analytics process and is used in many different domain areas. The purpose of this paper is to investigate matrix-factorization-based dimensionality reduction as a design artifact in predictive analytics. With the rise in availability of large amounts of...

Model evaluation – the process of making inferences about the performance of predictive models – is a critical component of predictive modeling research in learning analytics. In this work, we present an overview of the state-of-the-practice of model evaluation in learning analytics, which overwhelmingly uses only näıve methods for model evaluation or, less commonly, statistical tests which are...

Predictive modeling of habitat distribution of range plant species and identification of their potential habitats play important roles in the restoration of disturbed rangelands. This study aimed to predict the geographical distribution of Artemisia sieberi and find the influential variables in the distribution of A. sieberi in the desert rangelands of central Iran. Maps of environmental variab...

Predictive accuracy is the sum of two kinds of uncertainty–natural variability and modeling uncertainty. This paper addresses the quantification of predictive accuracy of complex simulation models from two perspectives. First, it recognizes that there is a difference between variability and modeling uncertainty; the former can not be reduced with more test information, while the latter can. We ...

Modeling is a pervasive feature in any engineering curriculum that is rarely taught as an explicit topic to engineering learners. The implicit inclusion of modeling often results in conceptions of models being primarily descriptive – visual and physical representations – that originate from everyday and coursework use. A broader understanding of modeling is achieved when students are given oppo...