def task_2_results():
kf = KFold(n_folds=k)
accuracies = []
for train_index, test_index in kf.split(y):
X_train = X_manual[train_index]
X_test = X_manual[test_index]
y_train = y[train_index]
y_test = y[test_index]
SVM.learn_svm(X_train, y_train, prefix+"task_2_model")
accuracies.append(SVM.test_svm_accuracy(X_test, y_test, prefix+"task_2_model"))
print "Accuracy for task_2:", np.mean(accuracies), "+-", np.std(accuracies)
return accuracies
def task_3_results():
kf = KFold(n_folds=k)
num_manual_features = len(X_manual[0])
accuracies = []
for i in range(num_manual_features):
accuracies.append([])
X_manual_np = np.asarray(X_manual)
for train_index, test_index in kf.split(X_content):
X_train = X_content[train_index]
X_test = X_content[test_index]
for i in range(num_manual_features):
y_train = X_manual_np[train_index, i]
y_test = X_manual_np[test_index, i]
SVM.learn_svm(X_train, list(y_train), prefix+"task_3_model")
accuracies[i].append(SVM.test_svm_accuracy(X_test, list(y_test), prefix+"task_3_model"))
for i in range(num_manual_features):
print "Accuracy for task_3 (" + str(names[i]) + "):", np.mean(accuracies[i]), "+-", np.std(accuracies[i])
return accuracies
def task_4_results():
kf = KFold(n_folds=k)
num_manual_features = len(X_manual[0])
accuracies = []
X_manual_np = np.asarray(X_manual)
for train_index, test_index in kf.split(X_content):
X_content_train = X_content[train_index]
X_manual_test = X_manual[test_index] # Just for structure, populated below
X_content_test = X_content[test_index]
num_test = len(test_index)
for i in range(num_manual_features):
X_np_train = X_manual_np[train_index, i]
SVM.learn_svm(X_content_train, list(X_np_train), prefix+"task_4_model")
for j in range(num_test):
X_manual_test[j][i] = SVM.load_svm(prefix+"task_4_model").predict([X_content_test[j]])[0]
X_manual_train = X_manual[train_index]
y_train = y[train_index]
y_test = y[test_index]
SVM.learn_svm(X_manual_train, y_train, prefix+"task_4_model_1")
accuracies.append(SVM.test_svm_accuracy(X_manual_test, y_test, prefix+"task_4_model_1"))
print "Accuracy for task_4:", np.mean(accuracies), "+-", np.std(accuracies)
return accuracies
