资源列表
myKmeans.m
- 模式识别学习中使用matlab编写的Kmeans算法实现的小程序-Learning to use pattern recognition matlab prepared Kmeans algorithm small program
ecoli
- 聚类是将数据对象分组成多个簇（Cluster），同一个簇内 部的任意两个对象之间具有较高的 ），同一个簇内 部的任意两个对象之间具有较高的 相似度，而属于不同簇 的两个对象间具有较高的 ，而属于不同簇 的两个对象间具有较高的 相异度。相异度可以根据描述对 象的属性值计算，对象间的距离是最常采用的度量指标。-Clustering is a data object into a plurality of clusters (the Cluster), with a clu
GP
- 基于贝叶斯理论的高斯过程代码，包含高斯过程回归分析，以及相关噪声处理和高斯过程分类，提供数据进行测试，-Gauss procedure code based on Bayesian theory, including Gaussian process regression analysis, and related processing and noise Gaussian process classification, to provide data for testing, etc.
Cart-tree
- 实现CART树回归，树的生成与剪枝过程，并与简单线性回归进行对比-Implement a regression tree generation algorithm when the leaf nodes indicate 3rd order polynomials. Test your program with the dataset and compare the results with those of simple linear regression
MachineLearning-wepe
- MachineLearning-作者wepe 及其学习的实用包 包含决策树，支持向量机，K-MachineLearning- OF wepe and learn practical package contains decision trees, SVM, KNN, etc.
CAN-code
- 自适应临近聚类算法/集群和投影聚类/自适应的邻居 -Clustering and Projected Clustering with Adaptive Neighbors. The 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), New York, USA, 2014
Part1
- 实现了500篇纽约时报新闻的数据挖掘，包括数据预处理、基本数据统计等-Achieved 500 New York Times news data mining, including data preprocessing, basic data statistics, etc.
SVC
- 建立LibSVM预测模型，基于网格算法、粒子群算法、遗传算法优化了模型参数，并由最终模型预测了给定切削参数下零件的粗糙度等级。-Establish LibSVM prediction model, grid-based algorithm, particle swarm optimization, genetic algorithm to optimize the parameters of the model, the final model prediction given by the c
EMGMONE
- MATLAB em algoritm first for learning you shoud be read matlab
WDEMTOE
- MATLAB em algoritm first for learning you shoud be read matlab 2
zhichixlj
- matlab 支持向量机的源代码，里面有经典的案例分析，可以运行-Matlab support vector machine source code, which has a classic case analysis, you can run
hopfield
- hopfield神经网络的实现，里面含有丰富的源代码，可以运行-Hopfield neural network to achieve, which contains a wealth of source code, you can run