用SVM方法制作的分类器1 Training Click “Learning “ from Toolbar or Menu, a dialog will appears like following : You can browse and choose the training sample data file(*.trn), or write the data file’s name into the text editor directly. And write down the tra
图像的贝叶斯分类，将模式识别方法与图像处理技术相结合，掌握利用最小错分概率贝叶斯分类器进行图像分类的基本方法-Bayesian image classification, the pattern recognition method and image processing technology, to master the use of the smallest misclassification probability of Bayes classifier for image class
The aim of this program is to analyse images and be able to class them depending of their nature. The support vector machine algorithm is used to classify the pictures. The training data is composed of 760 images, separated in 3 different classes (C
使用本规则包可以根据商品标题自动分类； 规则包是机器学习后保存的规则文件；
python 样例脚本：
print("Load test data...")
test_data = gen_train_data(filename)
print("Start accuaracy...")
f = open('test1.pickle', 'rb')
classifier = pickle.load(f)
f.close()
for d in test_data:
print(d[0],classi
