The following tasks forms part of the assignment and must be included in your logbook Task-1) For this task, download data_SVM.txt from Blackboard. This is a simple data set that contains 1000 entries with 2 features and corresponding class labels ( 0 or 1 ) for each entry. Snapshot of data (first two columns are features, and last column is the class label). Use the Python script for this task, but it needs to be modified to load the data. You can load the data as follows: DATA =np. loadtxt( 'data_sVM.txt' ) x= DATA [:,0:2] y=DATA[:,2] Apply the SVM algorithm to obtain a classifier and plot the results. - What is the percentage of misclassified points using your SVM classifier? - Try the algorithm for a range of different values of C parameter [0.01,0.1,1.0], and provide the results together with your understanding of the influence of the C parameter. - Compare your SVM results with those from the Perceptron in week-6