Download JAR files tagged by hamilton with all dependencies
NNge from group nz.ac.waikato.cms.weka (version 1.0.2)
Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules). For more information, see Brent Martin (1995). Instance-Based learning: Nearest Neighbor With Generalization. Hamilton, New Zealand. Sylvain Roy (2002). Nearest Neighbor With Generalization. Christchurch, New Zealand.
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Artifact NNge
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/NNge
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/NNge
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
bestFirstTree from group nz.ac.waikato.cms.weka (version 1.0.4)
Class for building a best-first decision tree classifier. This class uses binary split for both nominal and numeric attributes. For missing values, the method of 'fractional' instances is used.
For more information, see:
Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ.
Jerome Friedman, Trevor Hastie, Robert Tibshirani (2000). Additive logistic regression : A statistical view of boosting. Annals of statistics. 28(2):337-407.
Group: nz.ac.waikato.cms.weka Artifact: bestFirstTree
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Artifact bestFirstTree
Group nz.ac.waikato.cms.weka
Version 1.0.4
Last update 27. April 2014
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/bestFirstTree
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
Group nz.ac.waikato.cms.weka
Version 1.0.4
Last update 27. April 2014
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/bestFirstTree
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
paceRegression from group nz.ac.waikato.cms.weka (version 1.0.2)
Class for building pace regression linear models and using them for prediction.
Under regularity conditions, pace regression is provably optimal when the number of coefficients tends to infinity. It consists of a group of estimators that are either overall optimal or optimal under certain conditions.
The current work of the pace regression theory, and therefore also this implementation, do not handle:
- missing values
- non-binary nominal attributes
- the case that n - k is small where n is the number of instances and k is the number of coefficients (the threshold used in this implmentation is 20)
For more information see:
Wang, Y (2000). A new approach to fitting linear models in high dimensional spaces. Hamilton, New Zealand.
Wang, Y., Witten, I. H.: Modeling for optimal probability prediction. In: Proceedings of the Nineteenth International Conference in Machine Learning, Sydney, Australia, 650-657, 2002.
Group: nz.ac.waikato.cms.weka Artifact: paceRegression
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Artifact paceRegression
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/paceRegression
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/paceRegression
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
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