资源列表
pocket-PLA
- 贪婪感知器算法。R语言实现版本，每次会把最优的分类抓在手上-pocket perceptron learning of algorithm
Batch-Gradient-Descent
- 分别使用了批梯度下降法和牛顿法进行线性回归的测试。-Respectively the batch gradient descent and Newton s method of linear regression tests.
GMMPEM
- 代码给出了高斯分布下的EM算法的设计与实现-Code gives the design and implementation of a Gaussian distribution under the EM algorithm
py_ml
- 简单的人脸识别，及其他机器学习方法，使用scikit-learn。-machine learning using python
NLP
- 自然语言处理教程与项目总结,java与python描述均有。-NLP summary
Question1
- 找素数，找前五十个素数，十个一行，共五行-prime number
convnetjs-master
- 基于C#开发的深度神经网络网页版。将文件夹拖动至浏览器即可使用功能。包括CNN、DBN等多种深度学习思路。-Based on C# development of depth Neural Network Web version. Drag the folder to the browser functionality. Including CNN, DBN and other deep learning ideas.
Apriori
- 用Apriori算法进行频繁项挖掘,输入文件格式参见input中的例子。-Mining frequent item with Apriori algorithm, the input file format see input examples.
Clustering
- 对数据进行归类，采用了k-means,NMF以及谱聚类三种方法。其中， 谱聚类的效率比较低下。-Classify the data, using the k-means, NMF and spectral clustering three methods. Among them, the relatively low efficiency of spectral clustering.
SgdClassifier
- 随机梯度下降分类器。本实验的实验平台为eclipse，只需导入(import)即可运行。输出方式为控制台输出，能够提供的评价数据有test error, percision, recall以及F1-measure。-Stochastic gradient descent classifier. In this study, experimental platform for eclipse, just import (import) to run. Output of the console o
RandomForestaAdaBoost
- 随机森林，决策树以及adaboost分类器的java实现。随机森林和adaboost都基于决策树完成。-Random forests, tree and adaboost classifier java. Random Forest and adaboost are based on the decision tree is complete.
SVM
- SVM多分类算法的一些程序，有很多种类型，包括经典的四种工具箱，还有代价敏感支持向量机，超球面支持向量机等-Some programs about SVM multi-classification algorithm, there are many types, including the classic four toolbox, as well as the price-sensitive support vector machine, hypersphere support vector