The nature of statistical learning theory
The nature of statistical learning theory
Proximal support vector machine classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
On the algorithmic implementation of multiclass kernel-based vector machines
The Journal of Machine Learning Research
On Learning Vector-Valued Functions
Neural Computation
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This paper deals with the application of fast single-shot multiclass proximal support vector machine for fault diagnosis of a gear box consisting of twenty four classes. The condition of an inaccessible gear in an operating machine can be monitored using the vibration signal of the machine measured at some convenient location and further processed to unravel the significance of these signals. The statistical feature vectors from Morlet wavelet coefficients are classified using J48 algorithm and the predominant features were fed as input for training and testing multiclass proximal support vector machine. The efficiency and time consumption in classifying the twenty four classes all-at-once is reported.