Sentence examples for mixed type data from inspiring English sources

A simulated data set and a heart disease mixed type data set for proof-of-principle.

The dynamic validity index for numeric data was modified with a category utility measure in order to determine the optimal number of clusters in the mixed type data.

For mixed type data, ILLS is the best choice if one wants to find differentially expressed genes, but LS would be better for the other two purposes.

PRB performed the analysis of the gene expression data, considered the utilization of the DVI_CU measure and the k-prototypes algorithm for gene expression and phenotypic data, implemented the mod k-prototypes clustering algorithm and DVI_CU, applied them to the mixed type data and wrote the paper.

A framework for classifying mixed-type data in imbalanced datasets was proposed.

While we chose faultline-related tasks based on the requirements by domain experts in organizational management, the study findings can be generalized to representations and tasks involving distributions of clusters of multivariate objects in mixed-type data.

Her research interests are mainly in goodness-of-fit, multivariate techniques for mixed-type data, functional data analysis and she has published numerous papers on these topics in international journals.

Moreover, the combined fuzzy model MEMBAS/LAMDA works well in datasets with mixed-type data, since the same fuzzifying process (membership functions) is used for both feature selection and classification.

We investigate sample size calculation for before after experiments where the outcome of interest is binary and the enrolled subjects contribute a mixed type of data: some subjects contribute complete pairs of before- and after-intervention outcomes, while some subjects contribute incomplete data (before-intervention only or after-intervention only).

We have proposed modifying this algorithm by adding an objective function to support and weight multi-domain, mixed type biological data within the k-means clustering paradigm.

The effectiveness of this method has been previously demonstrated on problems involving mixed type of data (numerical, qualitative, symbolic intervals) [ 53].