资源列表
libsvm-ranksvm-3.20
- RankSvm:实现了RankSvm，使用blas依赖库-RankSvm: realized RankSvm, use blas dependent libraries
knn
- 这是一个简单的测试knn算法的代码，便于初学者学习和理解knn算法-This is a simple test knn algorithm code, for beginners to learn and understand knn algorithm
K-MEANS
- k-means聚类算法 用C++实现 聚类采用数据为二维数据 保存在当前目录下的data.txt文件中-K-means clustering algorithm C++ implementation
maxmin
- 数据挖据中聚类问题的实现 通过简单数据进行聚类分析 该聚类为最大最小聚类-According to the data mining, the clustering problem is achieved by using simple data to cluster analysis.
cengcijvlei
- 层次聚类分析也称系统聚类法或分级聚类法，是实际工作中采用最多的方法之一-Hierarchical cluster analysis, also known as system clustering or hierarchical clustering method, is one of the most used methods in practical work.
literature
- 对采集的专家文献进行分类的一个自写的Java代码-The collection of the expert literature to classify a self written Java code
NLPLibSVM
- libsvm分词训练集的java版本。包括libsvm.jar以及训练集样本-Libsvm version of the Java word segmentation training set. Including libsvm.jar and training set samples
minhash
- minhash的论文。mihash算法是常用的算法。-Minhash papers. Mihash algorithm is a common algorithm.
GPR
- 利用高斯过程回归建立软测量模型，主程序名为OnlineStage.m,包含数据，可以直接运行，亲测可用。-Gaussian process regression soft sensor model, the main program named OnlineStage.m, contains data that can be run directly, pro-test available.
PLS
- 带注释的PLS实例，包含数据，可直接运行。-PLS annotated examples, including data, can be directly run.
AI-Naive
- 利用Python实现朴素贝叶斯分类方法。实现程序具有普适性，同时附带测试数据。可以直接运行。-Python implementations utilizing Naive Bayes classification. Achieve universal program has also included with the test data. It can be run directly.
kalman
- 使用卡尔曼滤波进行位置预测，一共两种方法-Kalman filter location prediction