The time series data mining (TSDM) framework is a fundamental contribution to the fields of time series and data mining. Methods based on the time series data mining framework are able to successfully characterize and predict complex, non-parametric, irregular and chaotic time series. The time series data mining methods overcome limitations (including stationarity and linearity requirements) of traditional time series analysis technique by adapting data mining concepts for analyzing time series.
The time series data mining (TSDM) framework is a fundamental contribution to the fields of time series and data mining. Methods based on the time series data mining framework are able to successfully characterize and predict complex, non-parametric, irregular and chaotic time series. The time series data mining methods overcome limitations (including stationarity and linearity requirements) of traditional time series analysis technique by adapting data mining concepts for analyzing time series.
This compendium is a completely revised version of an earlier book, Data Mining in Time Series Databases, by the same editors. It provides a unique collection of new articles written by leading...
Data mining is the process of extracting knowledge from large amounts of data. It covers a variety of techniques aimed at discovering diverse types of patterns on the basis of the requirements of the...
Practical Time Series Analysis for Data Science is an accessible guide that doesn't require a background in calculus to be engaging but does not shy away from deeper explanations of the techniques...
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