The phrase "a small set of data" is correct and usable in written English.
It can be used when referring to a limited amount of information or data points in a specific context, such as research or analysis.
Example: "In our study, we analyzed a small set of data to identify initial trends before expanding our research."
Alternatives: "a limited amount of data" or "a minor collection of data."
Bell, like most handicappers, said it was difficult to make sweeping conclusions on such a small set of data.
Even though a small set of data is obtained, our method retains the morphologies of the EEG signals.
In general, a large data set does not improve the results, so it is more efficient to use a small set of data (400 pixels).
Though the 1H NMR spectra validation is based on a small set of data, it is believed that the spectra identified by PatentEye are of nearly sufficient quality that they constitute a resource of value to the community.
A practical way to avoid overfitting while simultaneously improving the estimation capability of the network is to create a small set of data from the training set for cross-validation.
In general, a large data set does not improve the results, so it is more efficient to use a small set of data (400 pixels). Figure 7 Performance of algorithms for different numbers of spectral pixels.
The goal is to extract a smaller set of data that can be analyzed, using any of the same visualization or analytical tools that would be used for other data types.
Granted, BillShrink is dealing with a smaller set of data than a search engine that can query any term, but the site's backend is more tech-heavy than you might think.
Hence, the suggested method should be thought of as a help for the analyst to filter out a smaller set of data to look at, rather than a method to be fully automated.
In contrast, supervisory physicians (AP/NFs) often give a disproportionate significance to a smaller set of data items that aid them in making the most critical decisions and care plans with certain data items being lightly regarded or even ignored.
As such, the covariance matrix of all features can be approximated as a block diagonal matrix, thereby facilitating us to accurately extract the correlation information required by movement decoding from a small set of training data.
