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TiMBL is a program implementing several Memory-Based Learning techniques. TiMBL stores a representation of the training set explicitly in memory, and classifies new cases by extrapolation from the most similar stored cases. Several metrics and algorithms are implemented in TiMBL: Information Gain weighting for dealing with features of differing importance (IB1-IG), and the Modified Value Difference metric for making graded guesses of the match between two different symbolic values. TiMBL is optimized for fast classification by using several indexing techniques and heuristic approximations (such as IGTREE and TRIBL). The current version contains an API which you can use to include Memory-Based classifiers in your own programs. The package contains the code, reference guide, and a few example datasets.

Current Version:   2.0

License Type:   Free for non-commercial research use, registration required

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Source Code Availability:   Yes

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  • Debian Package:   No
  • RedHat RPM Package:   No
  • Other Packages:   Yes

Targeted Platforms:

UNIX (SunOS,Solaris,Linux,HP-UX)

Software/Hardware Requirements:

C++ Compiler

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