Sentence examples for dataset shape from inspiring English sources
When evaluated using the challenging Maximum Unbiased Validation dataset, shape constraints were able to extract significantly enriched subsets of compounds for the majority of targets, and FOMS matched or exceeded the performance of both VAMS and an optimizing alignment method of shape similarity search.
In the attempt to cover the entire dataset shape space with a minimum number of reference shapes, the algorithm tends to leave 'holes' in the shape space, thus producing unequally sampled regions.
We find the following shapes among all 27 of the three-dimensional genotopes of type (b) that appear as subsets of the complete dataset: shape 56 (frequency: 6), 7 (5), 25 (4), 8 (3), 52 (3), 21 (23, 23 (2), 2 (1), and 20 (1).
The tree files used as an input file for CODEML were produced by Maximum Likelihood (ML) with PhyML [ 70] and using FindModel with AIC to select the model that best fit each dataset [T92+G (shape parameter = 1,085) for clade A and TN93+G+I (shape = 1.135; pinv = 0.164) for clade B].
Table 2 shows the best classification result for the skating dataset with shape context features.
Several techniques are used in this dataset for shape and leaf classification.
To search the dataset by shape similarity, the query fingerprint, to extend the analogy, is compared to the dataset fingerprints to find common reference shapes.
That is, it identifies and quantifies the different kinds of 'empty space' embedded in the data, which implicitly make up the dataset's shape.
The curves showed a similar shape as compared when using the full dataset (figure not shown, log rank test, p<0.001).
Each individual image is then mapped to an optimal, dataset-specific shape and appearance template space, derived by a diffeomorphic groupwise normalization method [ 16, 17].
For two datasets with shape parameter estimates of 9.0 and 16.7, the 2-parameter absolute sigmoid model had similar likelihood, and variability in likelihood and fit were also limited.
