Sentence examples for vectors of features from inspiring English sources

Traditionally, numerical machine learning deals with unstructured data, in the form of vectors: neural networks, graphical models, support vector machines, handle vectors of features that are assumed to be relevant for solving the problem at hand (classification or regression).

In particular, a k-NN approach can be used and it can also be assumed that the projections of the vectors of features follow a Gaussian distribution [42].

The best combination of techniques involves the usage of the k-NN method and the vectors of features based on the angular-radial transform (ART) coefficients.

Better results would be expected if more training elements of all the classes were available, thus allowing to use larger vectors of features in this procedure.

Note that there is no marked difference between the k-NN and the Gaussian method of classification using the projections of the vectors of features.

At this stage, the vectors of features extracted for the unknown symbols must be compared against a series of patterns of known symbols.

Address the issue that feature vectors of feature-rich data objects are high dimensional.

To maintain the overall appearance and smoothness of the original surfaces, the proper relationship should be formulated between the displacement vectors of feature points and those of the other points.

After selecting the final set of features and extracting the corresponding values we have to take into account that the distance between two vectors of feature values is calculated as the sum of the differences between the individual feature values.

The output file is a table that can be produced in four alternative formats, containing a vector of features for every object processed.

In SVM classification, a training example is represented using a vector of features and a label.