Sentence examples for data analytics methods from inspiring English sources

Data analytics methods are helpful tools to make generalizations about past experience [36].

Thus, data analytics methods have to supply a high degree of unsupervised automation in order to treat different types of data.

In our research we target to investigate how to support this systematic reflection process with educational data analytics methods and tools from both the design and the delivery of Inquiry-based educational designs (IED).

Digital Epidemiology is a new field that has been growing rapidly in the past few years, fueled by the increasing availability of data and computing power, as well as by breakthroughs in data analytics methods.

Table 2 Efficient data analytics methods for data mining Problem Method References Clustering BIRCH [44] DBSCAN [45] Incremental DBSCAN [46] RKM [47] TKM [42] Classification SLIQ [50] TLAESA [51] FastNN [52] SFFS [53] GPU-based SVM [43] Association rules CLOSET [54] FP-tree [32] CHARM [55] MAFIA [56] FAST [57] Sequential patterns SPADE [58] CloSpan [59] PrefixSpan [60] SPAM [61] ISE [62].

Social computing enables and serves technology-mediated social services and applications that in turn generate vast amount of complex social data; such data are managed and processed through Big Data tools; then insights and prescriptions are derived from data analytics methods and algorithms.

Using a design science research approach, this study aims to design and evaluate a 'big data analytics' method to support strategic decision-making in tourism destination management.

It's just that now, for the first time in thousands of years, we need to think more about using data analytic methods for developing stories.

The study is designed to standardize assessment of biomarkers across multiple sites as well as institute replicable quality control methods, and to use advanced data analytic methods to integrate these markers.

Tabulations and logistic regression were the data analytic methods.

A suite of data analytic methods from Scikit-learn [ 16]; such as decision tree [ 17], support vector machine (SVM) [ 18], and random forest [ 19] were applied in addition to associative mining.