Machine Learning Software Library
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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):
- 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.
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.