Sentence examples for tackles data from inspiring English sources

It tackles data incompleteness in the post-processing phase by means of the mean value at each dimension of each cluster for missing data in the same cluster after performing the self-organizing map on the incomplete data set in the complete data subspace.

Very little information can be derived from raw tackle data, though.

In our experience, a business' awareness and a readiness to tackle data theft or staff poaching are directly linked to its experience of such an event.

This week I'll tackle data roaming fees, which wireless providers charge when customers use their phones outside their service area.

"Kaggle's platform has the potential to change the way we tackle data analysis problems".

The approach illustrated by the case study can potentially be applicable for tackling data modeling studies for which data availability is a problem.

Conventional data mining algorithms are usually developed to tackle data in one specific representation, a majority of which are particularly for vector-based data.

In this paper, our work follows the kernel-based approach with vector quantization and the nearest prototype strategy by proposing a robust and effective incomplete educational data clustering algorithm, named VQ_fk_nps, where we tackle data incompleteness in the data space while doing clustering in the feature space.

Data analysis based on differential topology has long been primarily focused on data samples on univariate (scalar-valued) functions f : R n → R. Nonetheless, with the recent advent of high-performance computers and sensors of high resolution, we are more likely to tackle data samples of multivariate functions f : R n → R m, m>1.

Whereas the likes of Ometria and GoSquared are tackling data and analytics head-on, helping e-commerce sites up their game against the Amazons of the world, LoyaltyLion's data-driven platform enables online stores to offer a loyalty scheme for customers and reward them for various activities.

Crawford warns CIOs to be aware of business disruption based on the inability of average of CIOs to tackle data sciences, IoT and machine learning and the need for application integration with other lines-of-business outside of IT.