def drive_smo(train_filename, test_filename, kernel_type_in=None, C_in=None, eps_in=None): train_y, train_x = svm_read_problem(train_filename) if C_in is None: C_in = 1 if eps_in is None: eps_in = 1e-5 if kernel_type_in is None: kernel_type_in = "linear" test_y, test_x = svm_read_problem(test_filename) init(train_x, train_y, kernel_type_in, C_in, eps_in) driver() print "Training Accuracy:\n" print get_training_accuracy() print "Testing Accuracy:\n" print get_test_accuracy(test_x, test_y)
def drive_smo(train_filename, test_filename, kernel_type_in=None, C_in=None, eps_in=None): train_y, train_x = svm_read_problem(train_filename) if C_in is None: C_in = 1 if eps_in is None: eps_in = 1e-5 if kernel_type_in is None: kernel_type_in = 'linear' test_y, test_x = svm_read_problem(test_filename) init(train_x, train_y, kernel_type_in, C_in, eps_in) driver() print "Training Accuracy:\n" print get_training_accuracy() print "Testing Accuracy:\n" print get_test_accuracy(test_x, test_y)
def drive_smo_ng( filename , C = None , Tol=None , max_passes=None , Kernel= None ): y,x=svm_read_problem(filename) if C is None: C=1 if Tol is None: Tol=1e-5 if max_passes is None: max_passes=5 if Kernel is None: Kernel='linear' svm_ob=smo(x,y,C,Tol,max_passes,Kernel) svm_ob.driver() print svm_ob.get_training_accuracy()
def drive_smo_ng(filename, C=None, Tol=None, max_passes=None, Kernel=None): y, x = svm_read_problem(filename) if C is None: C = 1 if Tol is None: Tol = 1e-5 if max_passes is None: max_passes = 5 if Kernel is None: Kernel = 'linear' svm_ob = smo(x, y, C, Tol, max_passes, Kernel) svm_ob.driver() print svm_ob.get_training_accuracy()