Sentence examples for categories of features from inspiring English sources

Through our study, we propose four categories of features that reflect designers' concerns in judging review helpfulness.

Our approach is based on a clear separation between the two categories of features, and uses algebra, respectively coalgebra to formalise them.

Furthermore, for the cases where review ratings are not steadily available, we have proposed to use regression to predict and interpret review helpfulness with the help of the aforementioned four categories of features that are entirely extracted from review content.

A bag-of-soft-biometric features is made up of different categories of features: color, texture, local features, and geometry.

There are three categories of features: tweet influence: the importance of a tweet within the conversation where it appears is estimated using social influence.

Moreover, for person identification purposes, a bag-of-soft-biometric features is composed of different categories of features: color, texture, local features, and geometry.

Two major categories of feature selection methods are the filter method and the wrapper method.

There are three main categories of feature selection algorithms: filter, wrapper and embedded.

In this study, two different categories of feature extraction techniques are used, namely appearance-based and texture-based techniques.

Since most of those algorithms consist of both feature extraction and classification, we provide a survey on three categories of feature extraction methods, including the voxel-, vertex- and ROI-based ones, and four categories of classifiers, including the linear discriminant analysis, Bayes classifiers, support vector machines, and artificial neural networks.

Three categories of feature selection methods can be used: filters, wrappers, and embedded methods [ 242, 243].