In the paper, authors present a temporal data science algorithm for analyzing big COVID-19 epidemiological data, with focus on the temporal data analytics with.
time series analysis overview
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The primary goal of learning analytics is to understand and optimize learning, a process that occurs over time; thus a consideration of temporality is relevant ...
This paper introduces the reader to temporal data management, surveys state-of-the-art solutions to challenging aspects of temporal data management, and points ...
In this paper, I will discuss a number of Stata's capabilities in the area of time series modeling, including data management and graphics. I will focus on a ...
The implementation of high-performance computing in spatial-temporal data analytics could solve problems faced in complex operations and increase the ...
by TG Dietterich · Cited by 1086 — This paper formalizes the principal learning tasks and describes the methods that have been developed within the machine learning re- search community
Abstract. Statistical learning problems in many fields involve sequen- tial data. This paper formalizes the principal learning tasks and describes.
Emergence of sequence analysis in the social sciences. Examples from political science and history, from micro-sociology of the family, and from social mobility.
A fixed sample size experiment is one in which the sample size taken for experimentation is predetermined, while a sequential experiment involves monitoring incoming data to help determine an appropriate time to stop experimentation.
The purpose of Sequential Analysis is to publish contributions in both theoretical and applied aspects of sequential methodologies in all areas of statistical science.
Lag sequential analysis is a method for analyzing the sequential dependency in a serially sequenced series of dichotomous codes representing different system ...
Abstract—This study applies a machine-learning model to analyze marketing sequential data to improve the performance of sales forecasting.
Spatio-temporal data analytics refers to the analysis of data that has both temporal and spatial properties, i.e. the data that varies along both space and time ...
