Python实现Adaboost算法，数据集为horseColic马疝气病数据集，准确率和sklearn库中的adaboost算法一样。-Python implementation adaboost algorithm, the data set is horseColic horse hernia disease data collection, accuracy and sklearn library adaboost the same algorithm.

机器学习启蒙实战学习源码，回归模型，分类模型，聚类和相似度模型，推荐系统，深度学习等学习代码。(Machine learning, practical combat learning source,regression model, classification model, clustering and similarity model, recommendation system, depth learning and other learning code.)

使用python语言，借助sklearn库实现了多元线性回归的训练和预测(The training and prediction of multiple linear regression are realized by using Python language and sklearn Library)

generateclassifier.py Python脚本来创建文件digits_cls.pkl分类器。 performrecognition.py Python脚本测试分类。 digits_cls.pkl -数字识别的分类器文件。 photo_1.jpg测试图像1号测试分类器 photo_2.jpg测试图像号码2测试分类(generateClassifier.py - Python scr ipt to create the classifier file digits_cl