Sentence examples for data dimensions and from inspiring English sources

These new algorithms successfully eliminate the limit on the number of data dimensions, and thus enabled computation of contour trees even from time-varying and higher-dimensional data samples.

Soon, budding data analysts will be able to ask Power BI for possible explanations for why a certain number trended up or down, for example, and the service will look at all of the different data dimensions and present a number of possible explanations, together with a graphical analysis.

SWIFT tests all clusters resulting from step 1 for unimodality in all data dimensions and along the principal component axes.

Our proposed two-step framework includes (1) attribute filtering using Naïve Bayes (NB) to extract the most informative features and thus greatly reduce the number of data dimensions and (2) the subsequent higher order classification using Hidden Naïve Bayes (HNB).

The differences between all possible pairs of clusters with any overlap are measured by the Kullback Leibler (K L) divergence, and the most similar pair is merged if the resulting cluster would be unimodal along: (a) the linear-discriminant-analysis (LDA) dimension along which the pair is most separated, (b) all data dimensions and (c) the principal component axes.

The core idea of using GA was to simultaneously reduce the data dimension and optimize the classifier performance.

From PCA, five major principal components were extracted which perfectly reduced the data dimension and indicated possible anthropogenic sources.

From PCA, three major principal components were extracted which perfectly reduced the data dimension and also indicated possible anthropogenic sources.

The research demonstrated the use of dimensionality reduction to reduce the data dimension and to select only the most important attributes which can explain the target variable.

Having observed the low performance of applying mere LDA on our datasets at the initial stage of the study, we decided to first employ GA to reduce the data dimension and then apply LDA to improve the accuracy of final classifier.

The Zero-Training method and standard CSP were used with different data dimensions (12 and 4 resp).