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Machine learning library that performs several clustering algorithms (k-means, incremental k-means, DBSCAN, incremental DBSCAN, mitosis, incremental mitosis, mean shift and SHC) and performs several semi-supervised machine learning approaches (self-learning and co-training).
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To run the library, just double click on the jar file. Also, you can use the following command line:
Java -Xms1500m -jar "ML Library.jar"
to ensure that the java virtual machine has enough space to run.
You can find sample test files under code/Test. Test files for clustering part are under code/Test/InputFile which contains two chameleon datasets from:
http://glaros.dtc.umn.edu/gkhome/cluto/cluto/download
Also, you can find sample test files for self-learning and co-training under its corresponding folders. Mainly genes/miRNAs expressions downloaded from :
http://0-www.ncbi.nlm.nih.gov.elis.tmu.edu.tw/
Features
- Perform K-means Clustering Algorithm
- Perform Incremental K-means Clustering Algorithm
- Perform DBSCAN Clustering Algorithm
- Perform Incremental DBSCAN Clustering Algorithm
- Perform Mitosis Clustering Algorithm
- Perform Incremental Mitosis Clustering Algorithm
- Perform Mean Shift Clustering Algorithm
- Perform SHC Clustering Algorithm
- Measure Clustering F-measure, Jaccard, Rand and Rand Index Measures
- Perform Self-Learning Semi-Supervised Algorithm
- Perform Co-Training Semi-Supervised Algorithm
- GUI based Application
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