Performance Evaluation of Kernel SVM on Sparse Datasets with Large Attributes
Support Vector Machines (SVM) is a Machine Learning Algorithm which is used for Classiﬁcation and Regression in many applications. The vital characteristic of SVM is that the classiﬁcation decision function is formulated using very few points in the training dataset. We have provided the less publicized mathematical formulation of Hard Margin SVM Classiﬁer, Soft Margin SVM Classiﬁer and the Kernel Trick. In this paper we have used two sparse data sets, we found that Kernel SVM shows signiﬁcantly better generalization and prediction accuracy for sparse datasets. We have compared the classiﬁcation performance with other Machine Learning algorithms such as Logistic Regression, Neural Networks, Bayesian Network, KNN, Bagging and Random Forest.
 C. Cortes and V. Vapnik. Support vector networks. Machine Learning, 20:273-297, 1995.
 Joachims T. (1998) Text categorization with Support Vector Machines: Learning with many relevant features. In: Nédellec C., Rouveirol C. (eds) Machine Learning: ECML-98. ECML 1998. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence), vol 1398. Springer, Berlin, Heidelberg
 O. Chapelle, P. Haffner and V. N. Vapnik, "Support vector machines for histogram-based image classification," in IEEE Transactions on Neural Networks, vol. 10, no. 5, pp. 1055-1064, Sept. 1999.
 A. Ganapathiraju, J. E. Hamaker and J. Picone, "Applications of support vector machines to speech recognition," in IEEE Transactions on Signal Processing, vol. 52, no. 8, pp. 2348-2355, Aug. 2004.
 E. Osuna, R. Freund and F. Girosit, "Training support vector machines: an application to face detection," Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, USA, 1997, pp. 130-136.
 A. Vedaldi and A. Zisserman, "Efficient additive kernels via explicit feature maps," 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, 2010, pp. 3539-3546.
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