Sentence examples for datasets reflect from inspiring English sources

The Snow fall and Skating datasets reflect this situation.

Algorithms are only as good as their benchmark datasets, and those datasets reflect their creators' biases (conscious or not).

Yet, no systems based on limited datasets reflect the evolution of the whole organisms; rather, they focus just on the evolutionary modifications of the data in question.

None of the best DI values from the SVR models with the linear kernel among three datasets reflect the non-linear correlation of the Gabor energy and phase features.

Second, log datasets reflect the activities of a larger community as they record the interactions of all users of scholarly portals, including scientific authors, practitioners of science, and the informed public.

However, a number of caveats have to be discussed in interpreting these patterns (e.g., the NE LMD includes the well-studied Great Barrier Reef; certain taxonomists have concentrated on particular regions; and the datasets reflect the locations of recent surveys).

The experiments in [28], however, are limited to very simple toy datasets reflecting only one clustering aspect at a time.

This paper focuses on designing incremental Slope-one recommenders able to address dynamic datasets, reflecting their variations instantly without retraining the whole model.

The experimental datasets reflected both the initial non-equilibrium detachment process followed by near-equilibrium detachment later in the simulations associated with aggregate structure and fluid energy, with the more aggressive tillage systems exhibiting less time to reaching equilibrium.

The model is based on relationships established from 1311 field sites sampled across Australia at two depths (0 10 and ~ 60 80 cm) and 49 national environmental predictor datasets reflecting fundamental soil formation processes (e.g., climate, parent material, relief).

The aim of our formalization is to automatically label the target data, to attribute weights to samples of both source and target datasets reflecting their relevance, to select relevant samples for the training according to their weights, and to train a scene specialized classifier.