1. The Perceptron Algorithm (Primal Form) Repeat: until no mistakes made within the for loop return:. What is ?

2. The Perceptron Algorithm (Dual Form) Given a linearly separable training setand Repeat: until no mistakes made within the for loop return:

3. What We Got in the Dual Form Perceptron Algorithm?  The number of updates equals:  implies that the training point has been misclassified in the training process at least once.  implies that removing the training point will not affect the final results  The training data only appear in the algorithm through the entries of the Gram matrix, which is defined below:

4. The Margin Slack Variable of with respect to For a fixed value called the target margin, we define the margin slack variable of training point with respect to the hyperplane and as If then is misclassified by the hyperplane