Sentence examples for weighted learning from inspiring English sources

A composite adaptive locally weighted learning (LWL) control approach is proposed for a class of uncertain nonlinear systems with system constraints, including state constraints and asymmetric control saturation in this paper.

Shafi et al. [22] used two other datasets from PROMISE repository, JEditData and AR3; they applied 30 different techniques on them, and showed that classification via regression and locally weighted learning (LWL) are better than the other techniques; they chose precision, recall and accuracy as an evaluation performance metrics.

An enhanced BPNN with a weighted learning strategy is designed as the classification mechanism.

Across three phases, they belong to the cohort that contributes to the denominator of the weighted learning gain.

Figure 10 shows that the weighted learning algorithm matches quite closely the result from solving the Markov model after 100 rounds for β=0.9.

We say that a learner has mastered or learned a concept if they have mastered the corresponding set (or some subset) of weighted learning objectives.

A complete covariate shift process is divided into two stages: reweighting importance of training data, and training a weighted machine learning model for prediction on the test dataset.

The WCOR methodology makes use of metaheuristic algorithms to find the best set of rules, as well as their weights, when learning weighted linguistic fuzzy systems from data.

SIRIUS uses fragment intensities to distinguish noise and signal peaks, while the intensities were weighted lowly during learning (see [25, 26]).

For example, even though experience weighted attraction learning is very successful in modeling behavior in one-shot games with very small, finite strategy spaces, it is not successful in modeling behavior in repeated games with a continuum strategy space unless one wants to be involved in fine tuning.

If the history is set to use the current model stage (h=t+1), then (phi ) approaches 1 as time passes, placing more weight on prior beliefs, which is pure weighted fictitious play learning.