mainFeatures Extraction and Analysis of Time-Series - Summary

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Id: #578
System Name: feats
Name: Features Extraction and Analysis of Time-Series
Group Type: Programs

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FEATS intends to be a state-of-the-art implementation of time-series data-mining algorithms in C++. The todo ordered list is:
- Segmentation
- Symbolic Representation
- Clustering
- Indexing
Bindings to other languages (Python and R) will be done.

It is intented as a contribution to the UCR Time Series Data Mining Archive [1]. I will try to test the library on the data-sets of the archive, and to implement algorithms described there (after implementing my own algorithms, of course :-) ).

FEATS major goals are:
- flexibility
- efficiency

Flexibility because it must be a useful fondation to research scientists in time-series data-mining.
Efficiency because it must also be useful on real-world data-sets. For now, the goal is to tackle time-series fitting in the computer memory (1Go). Data-base connectivity for truely huge data-sets will be considered later. For research scientists, it should be useable as a benchmarcking tool (hence the need for an open source code to fight implementation bias).

The means to these ends are :
1) static polymorphism (aka template meta-programming)
Following principles form "Generative Programming", we will make every compile-time knowledge available to the compiler. For instance, heavy use of Boost::mpl or Boost::fusion is to be expected.
Use of coding conventions (such as only one argument) to enable better metaprogrammation (ie. forwarding, code weaving ).

2) relevent encapsulation
Computations can often be eliminated by reusing intermediate results, for example when computing segmentation with n+1 segments). This will be achieved by the use of Functors instead of functions to store and reuse the relevent data.

[1]Keogh, E. & Folias, T. (2002). The UCR Time Series Data Mining Archive Riverside CA. University of California - Computer Science & Engineering Department

Registration Date: Wed Jun 2 12:59:14 2004
License: GNU General Public License V2 or later
Development Status: 4 - Beta


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