Ambedkar Institute of Advanced Communication Technologies and Research AIACT&R

Delhi, India

Ambedkar Institute of Advanced Communication Technologies and Research AIACT&R

Delhi, India
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Raychaudhuri K.,Ambedkar Institute of Advanced Communication Technologies and Research AIACT&R | Kumar M.,Ambedkar Institute of Advanced Communication Technologies and Research AIACT&R | Bhanu S.,Ambedkar Institute of Advanced Communication Technologies and Research AIACT&R
Communications in Computer and Information Science | Year: 2017

A support vector machine (SVM) is a classification technique in the field of data mining, used for the classification of both linear as well as non-linear data. It learns the decision surface from two different classes of input samples and then performs analysis of new input samples. A neural network is able to learn without the explicit description of the problem or the need of a programmer. Another type of classification technique is the decision tree. In this paper, we are doing a comparative study of the above mentioned classification techniques by analyzing their performance on data sets. We will be comparing the inputs and the observed outputs. © Springer Nature Singapore Pte Ltd. 2017.

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