Sentence examples for samples for classification from inspiring English sources

The effective development of data mining techniques for the discovery of knowledge from training samples for classification problems in industrial engineering is necessary in applications, such as group technology.

Open image in new window Fig. 2 Plot of calculated values of SAR and EC of water samples for classification of irrigation water (after US Salinity Laboratory Staff, 1954).

While the kernel-based leaning classification methods [for instance, the support vector machines (SVM) method] try to pick out the informative samples for classification, thus these methods usually achieve higher recognition accuracy and at the same time maintain relative sparsity of the support vectors.

In order to generate the train and test samples for classification experiment, 577 samples (67%% of 861) are randomly selected as training patterns, and the rest 284 samples are considered as test set.

During testing, each 5 s musical piece represented by 41 feature (activation) vectors is considered as a sample for classification.

The numbers of samples available for classification analysis and survival analysis differed because the former was performed only on those samples that could be binarized into 'relapse' or 'no relapse' with 10 years of follow-up whereas the latter made use of all patients (with censoring), even those with no relapse but <10 years follow-up.

Finally, user-friendly software as a GUI was created based on the best PLS and PLS-DA models developed for prediction of diazinon contents in the samples and for classification of intact cucumbers by the absence/presence of diazinon residues, respectively.

The proposed over-sampling method generates useful synthetic samples for the classification of imbalanced biomedical data.

The experimental results on eight real-world benchmark datasets have shown that the proposed over-sampling method generates useful synthetic samples for the classification of imbalanced biomedical data.

This does not rely on training samples for artificial classification.

He then randomly selected 3,000 posts from the overall samples for manual classification.