Sentence examples for a sparse dataset from inspiring English sources

The automatic data collection led to a dense dataset of 161 compounds with annotations for both targets, and a sparse dataset of 2191 compounds with annotation in at least one target.

We, however, expect that regardless of the choice of imputation method this remained a sparse dataset with substantial limitations which should be acknowledged and carefully considered when applying this model for future simulation purposes.

We found (Additional file 2: Supplementary Materials) that the top interaction was not consistently validated (3/10) and, without precluding the possibility that no synergy effects with relevance to MDD exist in these candidate genes, conclude that the curse of higher order of dimensions attenuates the power to predict an interaction in a sparse dataset.

For the ChIP-chip dataset, we follow the procedure of Lee et al. (2002) and threshold the data at a P-value of 0.001, giving us a sparse dataset where the detections are robust, at the expense of a larger proportion of false negatives (Lee et al. estimate 6 10% false positives and that about one-third of the interactions are missed).

This is related to the issue of a selection of an appropriately sparse dataset for training (see [Ganesh et al., 2008; Yamashita et al., 2008] for a discussion of the fMRI case).

First datasets (dense sampling: dataset A; sparse sampling: dataset B) were simulated and re-estimated.

By not relying on a single sparse dataset characterised by thousands of noisy and correlated features, one contributes to the reduction of false positive and negative predictions.

With the proper optimization procedure and selection of hyperparameters, we demonstrate that deep architectures can be beneficial, even with a moderately sparse dataset.

First a sparse matrix dataset was generated using the newCellDataSet function.

Without this weighting scheme, a sparse association dataset would be completely dominated (visually) by the large number of objects forced to lie at the outside of the unit ball because most objects are 'very far' from most other objects.

We demonstrate that deep architectures can be beneficial even with a sparse biological dataset.