Understanding Support vector machine(SVM)

In this tutorial, we will be going to look at Support vector machine which is a very useful algorithm to solve certain prediction.

working of Support Vector Machine – SVM

From national security to medical surgery, image classification is the major tool used to overcome many impossible solutions. To support this statement we have an algorithm called as SVM (support vector machine) using binary classification algorithm resulting in the creation of a very powerful model which can classify image based on many input parameter in addition to this we bind this algorithm with a deep learning model resulting in creation very strong machine learning model

following steps are followed by support vector machine(SVM);

  • Support Vectors are simply the coordinates of individual observation. SVM is a frontier which best segregates the two classes
  • Distribute input parameter in X, Y coordinate of hyper plan
  • Draw various hyper plan so that that same class object can be segregated easily
  • selecting write hyper plan: maximizing the distances between nearest data point (either class) and hyper-plane will help us to decide the right hyper-plane. This distance is called a Margin
  • This is how the best hyper plan parameter is selected and then this parameter is used as the weight for the neural network

Application of SVM

  • Image processing
  • natural language processing

Conclusion

in this tutorial, we have learned the following

  • what is the support vector machine?
  • Algorithm of SVM

hope to see you in the next tutorial until then I would recommend having look on (Understanding Artificial Neural network (ANN)),

Enjoy learning

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