Sentence examples for the other dataset from inspiring English sources

The other dataset contains GPS coordinates of 13,799 taxis in 9 days in Shenzhen, China (SZ for short).

The SVM classifier was trained on the features using the data set of one of the experiments and applied it on the other dataset.

As indicated in earlier sections, the SVM classifier was trained on the features using the data set of one of the experiments and applied on the other dataset.

The other dataset was generated using the program InSillicoTEM (Vulovic et al., 2013) to incorporate near experimental microscopic effects including contrast transfer function and detective quantum efficiency of camera.

One dataset is stored as floating-point single-precision values, with each voxel value equalling the activity in MBq in the volume represented by that voxel, while the other dataset is stored as integers, where the sum of the integer values is the predefined number of histories for the MC simulation.

The samples in the other dataset were divided into five subsets of equal size.

The other dataset studied by van't Veer et al. [10] contains the gene expression profiles of 295 patients from the Netherlands, where 79 had metastasis and 216 were metastasis-free.

The 84,967 filtered SNPs in common were merged following the consensus method, i.e. missing calls in one of the datasets was filled from the other dataset, and mismatches between datasets resulted in a missing call in the merged dataset.

However, the USA breast cancer dataset [11] and the Netherlands dataset [10] had been obtained from different microarray platforms and also preprocessed using different methods, which makes it practically difficult to evaluate the robustness of the proposed classification method by training the classifier based on one of the datasets and evaluating its performance on the other dataset.

In order to evaluate the reproducibility of the pathway markers across different dataset, we performed cross-dataset experiments, where one dataset was used for selecting the pathway markers, and the other dataset was used for building the classifier based on the selected markers and evaluating its performance.

Given two independent datasets of similar size, where one dataset is used for training the classifier and the other dataset is used for evaluation, a robust classification scheme would show consistent classification performance if the training set were interchanged with the test set.