Sentence examples for the data weighting from inspiring English sources

Techniques, such as normalizing the data, weighting the data and using mean data, were developed, resulting in much stronger correlations.

Within the 'Methods' section, we describe the data used and their selection criteria and briefly outline the data weighting scheme.

In Section 2 we describe the data used, their selection criteria, and briefly outline the data weighting scheme.

After the data weighting stage, three different classification algorithms that included the k-NN (k-Nearest Neighbour), RBF NN (Radial Basis Function Neural Network) and SVM (Support Vector Machine) classifying algorithms have been used to classify the datasets.

In the data weighting method, the data sets belonging to each class within the dataset are first calculated by using k-means clustering method, after which the measures of central tendency belonging to each class are calculated, as well.

In the second stage, on the other hand, 3 different classification algorithms containing k-NN (k-nearest neighbor), extreme learning machine (ELM) and support vector machine (SVM) were used to classify 9 different urban land covers after the data weighting method.

Taking the infinite variance limit on Q to mitigate the bias in y leads to the data weight matrix (26 which can be used in the usual weighted least-squares solution.

(c) The result when the data weight is a constant.

where the data weight w x,y) ranges from 0 to 1.

To emphasize the inhomogeneous design of the data weight, we call this equation inhomogeneously screened Poisson equation.

We handle this problem by designing the data weight function w x,y) in a spatially varying manner.