Sentence examples for high dimensionality of data from inspiring English sources

Our investigation regarding the second topic focuses on specific challenges Deep Learning faces due to existing problems in Big Data Analytics, including learning from streaming data, dealing with high dimensionality of data, scalability of models, and distributed and parallel computing.

Information overload, data interconnectivity, high dimensionality of data and pattern extraction also pose major hurdles.

The high dimensionality of data has challenged the efficiency and reliability of clustering algorithms for quite sometime.

However, the large scale and high dimensionality of data have posed obvious challenges in data mining, storage, and integration.

Besides, the existence of high dimensionality of data and multiple polymorphisms has also increases the computational complexity of traditional statistical approaches to analyse large scale genetic data.

In addition, deducing the complex network structure from data remains an open problem partially due to the lack of prior information, relatively smaller sample size and the high dimensionality of data (number of possible nodes) [ 13, 14].

Contact: [email protected] The analysis of gene expression data in the field of systems biology is a challenging problem for a number of reasons, not least because of the high dimensionality of the data and relative dearth of data points.

Similarly, personal genomic high-throughput sequencing not only increases the volume and velocity of data but also adds to the high dimensionality of the data [7].

Reliable pattern classification is challenging due to the high dimensionality of fMRI data, the small number of available data sets, interindividual differences, and dependence on the acquisition methodology.

The high dimensionality of potential data types mandates standards to represent data in a uniform manner.

Ordinary multiple regression is seldom appropriate in the context of genetic data, due to the high dimensionality of the data and the correlation structure among the predictors.