Java Machine Learning Library (Java-ML)
Download
Mailing list
API documentation
Support, bugs and features
Links
Cite Java-ML
Documentation
Getting started
Finding documentation
Installing the library
Basic terminology
Data manipulation
Creating an Instance
Creating a Dataset
Load data from file
Store data to file
Normalization
Sampling and bootstrapping
Clustering
Clustering basics
Cluster evaluation
Weka clustering
Feature selection
Feature scoring
Feature ranking
Feature subset selection
Ensemble feature ranking
Weka attribute selection
Classification
Classification basics
Evaluate classifier on a dataset
Classification cross validation
Weka classifier
Databases
Developer documentation
Getting the source code
Running regression tests
References
Cluster evaluation measures
Clustering algorithms
Navigation
Download
Mailing list
API documentation
Support, bugs and features
Links
Cite Java-ML
Home
Data manipulation
Tue, 05/04/2010 - 07:21 — Thomas Abeel
Basic manipulation techniques to handle Datasets and Instances
Creating an Instance
Creating a Dataset
Load data from file
Store data to file
Normalization
Sampling and bootstrapping
Creating an Instance ›
Printer-friendly version
Other sites
Java-ML @ MLOSS
Java-ML @ Ohloh
Java-ML @ Sourceforge
Java-ML @ FishEye