Sentence examples for classification dataset from inspiring English sources

To test the performance of this new approach, twenty different well-known classification dataset benchmark problems from the UCI dataset were used.

Finally, for the classification, we propose the use of a deep learning classifier, which is pre-trained with a regression to hand-crafted feature values and fine-tuned based on the annotations of the breast mass classification dataset.

We have collected such rationales, in the form of substrings, for an existing document sentiment classification dataset.

The dense P-gp/BCRP dataset was therefore encoded into a 4-class classification dataset.

Commonly [3, 4], to evaluate classifier performance, the classification dataset is divided into two subsets of the same size.

The data source was the Shambaugh (2017) exchange regime classification dataset, which covers yearly observations for our whole period of analysis.

The empirical validation on five sentiment classification datasets demonstrates the effectiveness of FDBN and AFD methods.

Using 15 different classification datasets, we systematically investigate to what extent BP really depends on weight symmetry.

The NEA was tested on five real-world classification datasets and three well-known datasets for time series forecasting (TSF).

We have conducted experiments over 60 classification datasets, using 42 different types of decision tree ensembles, to test our hypothesis.

With six benchmark classification datasets, we demonstrate that the proposed approach is effective and competitive with well-established learning methods.