Sentence examples for approaches for data reduction from inspiring English sources

Two approaches for data reduction at this stage were considered: (1) labeling the interesting attributes by domain expert and (2) development of an adaptive learning algorithm for automatic attribute selection.

Several alternative approaches for data reduction were evaluated, including using the model fits from one of the other nonlinear models, using the fit for the linear model, and fitting the data to the exponential model using a defined value for the plateau based on results from other data sets.

The authors employed the first approach for data reduction.

The most common approach for data reduction is principal component analysis, that is, calculating independent linear combinations of the original variables that maximize the resulting variability (Myers 1990).

The approach is effective for data reduction, but it requires to be implemented with very large-scale cluster data deduplication systems [12].

The data generated were transcribed verbatim and content analysis approach was used for data reduction, naming data, obtaining analytical code and determining categories and themes.

Approaches to analyze mass spectral data using unsupervised and supervised data mining operations would greatly benefit from tools that effectively allow for data reduction without losing important diagnostic information.

This allows for data reduction.

CATPCA is often used for data reduction.

There are two modes for data reduction, i.e., 'sum' reduction mode and 'skip' reduction mode.

Probabilistic models were introduced for data reduction.