Search Results for "git:/git.code.sf.net/p/docfetcher/code"

This project is intended to provide Git access to the code of the original project, TA-Lib, which uses Subversion. It is intended for system integrators wishing to use TA-Lib in their Git-managed project through Git submodules or subtrees. No actual development is being done here; all development happens in the original project.

A much improved Linux/Perl implementation of the Murder Accountability Project's Serial Killer Algorithm. This module was tested with the "SHR76_19.csv" available from www.murderdata.org/p/data-docs.html. This module provides functions to prepare the data, upload to a database and view the identified clusters. Download SHR76_19.csv (23/03/2021) - https://www.dropbox.com/s/ye37woe6et05qgs/SHR76_19.csv.zip?dl=1 For information on this algorithm and the Murder Accountability Project please visit: www.murderdata.org. ...

C-squares is an easily implemented method for storage, querying and display of spatial data locations, based on a hierarchical, grid-based representation of the Earth' surface. Source code for encoding, decoding, mapping, etc. is provided via this site. Additional support is available by contacting the system developer, Tony.Rees@marinespecies.org; see also the c-squares home page at http://www.cmar.csiro.au/csquares/ .

MicroGP (µGP, ugp) is a versatile optimizer able to outperform both human experts and conventional heuristics in finding the optimal solution of hard problems. It is an evolutionary algorithm since it mimics some principles of the Neo-Darwinian paradigm. ⚠️ A new version is available on https://github.com/squillero/microgp4

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This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text. The method is based on SVM but other ML algorithms can be adopted.

LDIFF is an enhanced language-independent line differencing tool built upon the Unix diff and overcomes its limitations in determining whether an artifact line has been changed or is the result of additions and removals