Data Mining Algorithms In R
Publisher: Wikibooks 2010
In general terms, Data Mining comprises techniques and algorithms, for determining interesting patterns from large datasets. There are currently hundreds (or even more) algorithms that perform tasks such as frequent pattern mining, clustering, and classification, among others.
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by I. Androutsopoulos, G. D. Ritchie, P. Thanisch - arXiv
This paper is an introduction to natural language interfaces to databases (NLIDBs). Some advantages and disadvantages of NLIDBs are then discussed, comparing NLIDBs to formal query languages, form-based interfaces, and graphical interfaces.
by Christian S. Jensen - Aalborg University
Topics covered: the semantics of temporal data, the design of data models and languages for temporal data, the design of databases expressed in terms of temporal data models as well as temporally enhanced design of conventional databases.
by Adrienne Watt - BCcampus
The purpose of this text is to provide an open source textbook that covers most introductory database courses. This edition covers database systems and database design concepts. New to this edition are SQL info, additional examples, and exercises.
by Graham Williams - Togaware Pty Ltd
Data mining is about building models from data. We build models to gain insights into the world and how the world works. A data miner, in building models, deploys many different data analysis and model building techniques.