test.py 文件源码

def adaboost_predict(training_samples, training_labels, test_samples, test_lables,n_estimators=50, learning_rate=1.0):
    from sklearn.ensemble import AdaBoostClassifier

    clf = AdaBoostClassifier(n_estimators = n_estimators, learning_rate =learning_rate)

    t0 = time()
    clf.fit(training_samples,training_labels)
    training_time = round(time()-t0, 3)

    t0 = time()
    pred = clf.predict(test_samples)
    test_time = round(time()-t0, 3)

    from sklearn.metrics import accuracy_score

    acc = accuracy_score(pred,test_lables)

    no_features = np.array(training_samples).shape[1]
    training_samples = np.array(training_samples).shape[0]
    test_samples = np.array(test_samples).shape[0]

    with open("Temp\\results.txt","w") as outfile:
        outfile.write("Alogirthm : {}\n".format("Adaboost"))
        outfile.write("Estimators  = {}\n".format(n_estimators))
        outfile.write("Learning rate = {}\n".format(learning_rate))
        outfile.write("No of features : {}\n".format(no_features))
        outfile.write("No of training samples : {}\n".format(training_samples))
        outfile.write("No of test samples : {}\n".format(test_samples))
        outfile.write("Training time : {}\n".format(training_time))
        outfile.write("Test time : {}\n".format(test_time))
        outfile.write("Accuracy : {}\n".format(acc))

    with open("Temp\\result_labels.csv","wb") as outfile:
        np.savetxt(outfile,pred)