Sentence examples for classification of input from inspiring English sources

Exact(4)

Second, an automated quality-based score level fusion scheme is proposed for the classification of input MW images.

One way, which proved successful in the NUSAP method, for reduction of assessment variables is a classification of input variables and a consequent sensitivity analysis to discern highly relevant input variables [25].

Depending on the number of input variables, it creates principal components (PC's) representing the maximum variability in information data and its variance in descending order (PC1, PC2, PC3, etc).. Usually, the first two components (PC1 and PC2) are found to be the best means to carry out the classification of input variables.

In our model, we followed the same classification of input, process, and output variables as in the Gijselaers and Schmidt (1990) model but at the micro level.

Similar(56)

A classification of inputs and parameters was made in two subsets: the former – spatially distributed – to be selected among different options, the latter – lumped – to be calibrated.

The LSM uses spiking neurons connected by dynamic synapses to project inputs into a high dimensional feature space, allowing classification of inputs by linear separation, similar to the approach used in support vector machines (SVMs).

Figure 6 Color classification of an input image using two different classification schemes.

This leads to the creation of a big number of groups or to an inadequate classification of the input pattern.

The results lead to a classification of desirable input and output partitions and a parametric design of structural invariants.

unsupervised clustering of sequences from unlabeled data, given the desired number of clusters; supervised classification of new input sequences, given a set of labeled training sequences.

In this framework, we deal with two problems: (i) unsupervised clustering of sequences from unlabeled data, given the desired number of clusters;   (ii) supervised classification of new input sequences, given a set of labeled training sequences.  .

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