Sentence examples for solve pattern from inspiring English sources

Kernel methods such as support vector machines are a powerful technique to solve pattern recognition problems.

Dictionary learning approaches have been widely applied to solve pattern classification problems and have achieved promising performance.

This review intends to provide an integrative overview of the computational literature analyzed in the context of the problem of classification (odor discrimination) and regression (odor concentration estimation), particularly identifying key computational ingredients necessary to solve pattern recognition.

Since the constructed hyperplane has the largest distance to the nearest training data points of any class, SVMs in general have lower generalization error than other classifiers, and hence have been commonly used to solve pattern classification problems which have limited training samples [38, 96, 97, 98].

Perhaps our community of users can come up with novel ways to solve pattern-matching problems like that.

This is in sharp contrast with the human literature, where it has been shown that around 50%% of participants who learn to solve patterning problems generalize according to the opposites rule (Wills et al. 2011; see further analysis reported in Wills 2014).

Support Vector Machine (SVM): An SVM is a machine-learning mechanism for solving pattern recognition problems.

Artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving pattern recognition problems.

To cope with the knowledge acquisition bottleneck, the authors propose a new architecture combining rule-based reasoning (RBR), case-based reasoning (CBR) and knowledge acquisition technology in a system which solves pattern search problems.

In particular, Radial Basis Function (RBF) networks are well suited to solving pattern classification problems due to their simple topological structure and their capability for faster learning.

Now, a question which naturally arises is how software developers select the right design patterns from all relevant patterns to solve design problems in the software design phase.