The Aim of this project is to provide a collection of reusable Algorithms which can be used effectively in different scenarios.
Algorithm implementations are in Java. Objective here is to implement algorithms which should be more efficient than the JDK implementation and also to create a platform for the researchers who works on DataMining, Encryption algorithms, ect.. to collaborate and contribute to this project.
GAKNN is a datamining software for gene annotation data. GAKNN is built with k- Nearest Neighbour algorithm optimized by the genetic algorithm. Gene annotation datasets saved under .csv or .arff formats with Gene Ontology or FunCat categorization can use GAKNN to predict gene functions.
A general recommender system with basic models and MRA
Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide...
KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for datamining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
This project intends to create an indexing search engine, for knowledge management. The primary object is to apply an information retrieval core. And implement a knowledge data discovery theory such as dataminingalgorithm, text mining.
musicomp is a program which most important element is an evolutionary algorithm which uses datamining methods as a fitness function to generate monophone melodies.
Flash/PHP adaptation of the XTEA encryption algorithm. Allows encryption/decryption of sensitive data using 128-bit key. May be used for network data (HTTP) or offline for implementations like secure CD-ROM projects.
Weka++ is a collection of machine learning and dataminingalgorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.