Orange Modules
Orange modules are intended to extend basic Orange's functionality, or provide wrappers for easier use of some data mining techniques. They are already included in normal Orange distribution. Following set of pages provides description, demos and examples for selected modules.
Note: The documentation posted on the web is updated from the CVS in
real-time and refers to the latest snapshot of Orange. If you encounter
any inconsistencies please compare the standalone documentation with the
one on the web.
- orngAssoc
- A few things for association rules.
- orngBayes
- Wrapper around Orange's naive bayesian learner that makes it easier to use m-estimation; it can also print out the model.
- orngC45
- A module with a function that prints out C4.5 trees in exactly the same format as Quinlan's C4.5.
- orngCI
- Constructive induction (function decomposition methods, HINT, Kramer's constructive induction method).
- orngCN2
- A set of classes and functions for learning rules (based on CN2).
- orngDisc
- Wrapper around Orange's categorization techniques for continuous attributes.
- orngEnsemble
- Bagging, boosting,
random forests.
- orngEval
- Obsolete, included for compatibility with past version of Orange. Use orngTest and orngStat instead.
- orngFSS
- Feature subset selection.
- orngImpute
- Imputation wrappers for learners and classifiers.
- orngLinProj
- Implements the FreeViz method by Demsar et al.
- orngLookup
- Functions for working with classifiers with stored tables of examples.
- orngLR
- Wrappers for easier use of Orange's classes for logistic regression
- orngMDS
- Multidimensional scaling.
- orngMisc
- Miscellaneous functions, including various counters and selections of optimal objects in a sequence.
- orngMySQL
- Interface to MySQL.
- orngNetwork
- Network analysis and layout optimization.
- orngOutlier
- Simple outlier detection.
- orngReinforcement
- Reinforcement
learning.
- orngSQL
- A new interface to any PEP 249 compliant RDBS. Supports both MySQL and Postgres.
- orngSOM
- Self-organizing maps.
- orngStat
- Computation of various statistics such as accuracy, sensitivity, specificity, and area under ROC from the experimental data from module orngTest.
- orngSVM
- Support vector machines.
- orngTest
- Data sampling and testing of learners, for instance cross-validation, leave-one out, random sampling, etc. The results can be used by orngStat to compute various statistics.
- orngTree
- Wrapper around Orange's classification tree inducer. Most notably, implements tree printout and visualization.
- orngVizRank
- Implements the VizRank method by Leban et al.
- orngWrap
- Classes for tuning arguments using internal cross-validation and for searching for threshold for optimal classification accuracy.
- orngCA
- Class for calculating
correspondence analysis.
- orngTextCorpus
- Text
Corpus module is the base for textual processing in Orange. It is used
to load textual data and to perform basic preprocessing.
Additional modules for data mining (clustering, SVM wrapper for
probability estimation, logistic regression, density estimation...)
have been prepared by Aleks Jakulin and are accessible via his pages.