Using Support Vector Machines for Numerical Prediction

Using Support Vector Machines for Numerical Prediction

We present a new methodology for prediction of numeric data using only classifiers for discrete data such as C4.5/J4.8 and/or support vector machine (SVM). We have used the "one-vs-all" approach to discretize the numeric data into binary and then used support vector machine (SVM) with boos...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Hussain, S., Khamisani, V.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Boosting
classification
Decision trees
Equations
Machine learning
numerical prediction
Predictive models
Regression analysis
Regression tree analysis
Support vector machine
Support vector machine classification
Support vector machines
Testing
WEKA
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Beschreibung
Zusammenfassung:We present a new methodology for prediction of numeric data using only classifiers for discrete data such as C4.5/J4.8 and/or support vector machine (SVM). We have used the "one-vs-all" approach to discretize the numeric data into binary and then used support vector machine (SVM) with boosting using free Weka toolkit. Empirical study was carried on real datasets taken from University of California, Irvine (UCI) machine learning repository.
DOI:10.1109/INMIC.2007.4557695