Sentence examples for using a given dataset from inspiring English sources

By exposing the problem to a large number of participants proficient in different analytical techniques, crowd competitions can very quickly advance the technical frontier of what is possible using a given dataset.

Less well studied is whether a given predictive signature that has been identified using a given dataset is also predictive in additional unrelated datasets.

In the narrative review, key statistics are presented either by paper or by mapping algorithm, where a mapping algorithm is defined as prediction of EQ-5D from one source measure (or set of measures) to EQ-5D using a given dataset.

This demonstrates the generalization ability of abstract representations extracted by Deep Learning algorithms on new/unseen data, i.e., using features extracted from a given dataset to successfully perform a discriminative task on another dataset.

This technique reconstructs a given dataset using different propagation speed values and calculates the Shannon entropy to measure their focal quality.

We compared individualized FAIME scores between two cohorts of patients (tumor versus normal) for a given dataset using a standard t-test.

While the estimated binding signal is of good utility and can be conveniently computed for a given dataset using our software package, by extension, we can envision a complete ChIP-seq analysis methodology where the raw ChIP-seq signal would be subjected to a comprehensive multistage decomposition process, taking into account all relevant control datasets at the same time.

Mainly PCA is a projection method used for reducing dimensionality in a given dataset by capturing the most variance by a few orthogonal subspaces called principal components (PCs).

Like other machine learning algorithms, SVM has the ability to recognize patterns in a given dataset (used for training), and the resulting models can then be tested with previously unseen examples and new predictions can be made accordingly.

Note that usually the first eigenvalue corresponds to the trend of a given dataset when using SSA.

In typical settings, standardization is performed using the mean and SD of a given dataset, mostly the cancer-only cohort data, thus y ¯ / n indicates how much the given sample's overall pathway gene expression deviates from the center of the cancer samples.