Sentence examples for methods in machine from inspiring English sources

Clustering methods in machine learning may benefit from borrowing metaphors from physics.

On the other part, genetic programming method is one of the most powerful methods in machine learning field and could be utilized for non-linear regression problems.

Both qualitative and quantitative methods in machine learning can be adopted in the MDM process to accomplish different tasks in materials discovery, design, and optimization.

Teams that adopted and embellished standard methods in machine learning such as the lasso (a variant of subspace regression) and k-nearest neighbors (a type of local estimation) predicted protein and mRNA expression well.

Feature selection methods in machine learning can broadly be divided into filter, wrapper and embedded methods.

By combining the nondestructive device and dimension reduction method in machine learning, this paper analyses the scatter plot of two cracks in 2d and the fitting surface in 3d and give the quantitative index for determining the performance of used methods.

We originally proposed a probabilistic model to characterize the similarity between ATC codes by using a semantic method in machine learning [24], and then to infer the TS.

The analysis of physical datasets using modern methods developed in machine learning presents unique challenges and opportunities.

The desire to uncover features in the data robust to processing steps and parameter choice has led some investigators to adopt a nonparametric "train-test" statistical approach similar to methods used in machine learning [22] [24].

We then tested side by side the performance of the unsupervised clustering method, which is becoming standard in neuroscience, versus the performance of representative algorithms from some of the most popular supervised classification methods used in machine learning.

In fact, the major differences among tools are the consensus sequences they used for the comparison with the input sequences, the statistical models applied to this comparison, and the training methods implemented in machine learning approaches, which will be introduced later in this section.