Machine Learning Software Library

A Machine Learning Software Library is a data science library that implements and provides an interface to a machine learning algorithm.

• Context:
  • It can be used to solve a Machine Learning Task.
  • It can be used to build a Machine Learning-based System.
  • It can be a member of a Machine Learning Environment.
  • It can contain and expose a Statistics Library, Numerical Analysis Library, ...
  • It can be a member of Machine Leaning Framework.
• Example(s):
  • Weka Software Library.
  • FACTORIE Software Library.
  • MALLET Software Library.
  • MLC++.
  • scikit-learn Python Library.
  • Spark MLlib.
  • …
• Counter-Example(s):
  • C4.5 System, because it cannot be directly accessed as a program function.
  • NLP Software Library.
  • Statistics Library.
  • Numerical Analysis Library.
• See: Data Mining Tool.

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References

2005

• http://www.cs.waikato.ac.nz/ml/weka/index.html
  • Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

2001

• http://www.sgi.com/tech/mlc
  • QUOTE: MLC++ is a library of C++ classes for supervised machine learning. The MLC++ utilities were created using the library.

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