Table 2.

Comparative analysis SVM with other classification approach

S. No	Algorithm	Drawback
1	Decision tree classification	This classification technique performed poorly on small datasets and in our proposed model we have worked on small datasets on which SVM is better and effective [35]
		It is affected by the overfitting of datasets but SVM is free from the overfitting problem [35]
2	Random forest classification	The random Forest Classification algorithm is also affected by the overfitting of datasets and SVM is not sensitive to overfitting [35]