Sentence examples for machines and random from inspiring English sources

Our analysis includes several classification techniques (multilayer perceptrons, support vector machines and random forest) and compares their performance using different configurations to define the best classification method.

However, in many general and non-vision tasks, neural networks are surpassed by methods such as support vector machines and random forests that are also easier to use and faster to train.

Three clustering analyses (linear discriminant analysis, support vector machines, and random forest) and three multivariate regression methods (stepwise multiple linear regression, MLR; partial least squares regression, PLSR; and penalized spline) were used for pattern recognition and to develop the petroleum predictive models.

For the present section, initially the training set and the independent validation set are described, followed by the main modelling methodologies used, namely support vector machines and random forests.

Some of them, together with several emerging techniques, such as gradient boosting machines and random forests, have been recognized through notable load forecasting competitions [5, 6, 7, 8, 9].

Traditionally, univariate biological activities are predicted using a range of methods, including classical regression, support vector machines and Random Forests.

Models have been built using multiple learning algorithms including support vector machine and random forest.

As the classifiers, we have tried support vector machine and random forest of decision trees.

Several approaches in the literature have been proposed for interpreting local and global QSAR models based on support vector machine and random forest techniques [46, 47].

Amongst them, support vector machine and random forest had the best performance.

Using 10-fold cross validation for parameter optimization and resampling analysis for evaluation, support vector machine and random forest outperformed the other machine learning methods.