Sentence examples for statistical learning approaches from inspiring English sources
With roots in computer science and statistics, statistical learning approaches offer a credible option: These methods take a more inductive approach to building a model than is done in traditional regression, allowing the data greater role in suggesting the correct relationships between variables rather than imposing them a priori.
Having reduced the descriptors necessary for modeling elastic constants, statistical learning approaches may then be used to predict the reduced knowledge-based required as a function of the constituent characteristics.
We connect here statistical learning approaches in cognitive science, which are rooted in the sensitivity of learners to local distributional regularities, and network science approaches to characterizing global patterns and their emergent properties.
Which kinds of statistical learning approaches and the associated properties are appropriate for human tracking?
Although various statistical learning approaches were explored for the systems, logistic regression proved to be the most accurate method in all cases.
Machine learning or statistical learning approaches have been widely used to classifying and stratifying cancer patient data based on gene expression data [ 5- 7].
In this study, we demonstrate that a statistical learning approach using three features or material descriptors related to the chemical bonding and atomic radii of the elements in the alloys, provides a means to predict transformation temperatures.
To select the GHMs most significant for face recognition, a statistical learning approach is adopted.
To confirm the results of the unsupervised cluster analysis, we employed a supervised statistical learning approach.
Obtained results demonstrate more accurate power predictions can be reached by statistical machine learning approaches.
One reason for this might be that most (Q SAR models are the results of applying statistical machine learning approaches to chemical datasets and the resulting models are sometimes opaque and it is commonly not an easy task to extract the reasoning behind a prediction.
