资源列表
KMeans
- 数据聚类算法 kmeans 算法 ,使用MATLAB实现，文中的代码注释为中文，更易于实现-data mining algorithm , clustering algorithm , k_means algorithm
Bayesian-networks-for-Data-Mining
- 贝叶斯网络的介绍及其在数据挖掘和模式识别中的应用-Introduction Bayesian network and its application in data mining and pattern recognition
gSpan6.tar
- 频繁子图挖掘算法，非常经典，值得学习一下。-subgraph mining
The-optimization-of-K-means
- 对k-means算法的优化，通过优化初始聚类中心的选择-The optimization of K-means algorithm by improving the selection of initial clustering centers
recsys-challenge2015
- 本代码实现了 recsys challenge2015数据集分析的算法，对数据挖掘和推荐系统的学习很有帮助~！-This code implements recommend algorithm based on recsys challenge2015 data set , which definitly would helpful for studying Data mining and Recommendation system !just enjoy
xin-k-means
- 此程序中直接是关于具体数据的聚类划分，直接给出相应的数据。-This program is directly of clustering on specific data directly gives the corresponding data
LSASummarization-a-paper
- lsasummarization 用 lsa 来干文摘的工作。 配套论文-lsasummarization leverages lsa language model in the task of text summarization
kernel-kmeans
- 实现kernel k-means 聚类，可以处理非线性数据-Implement kernel k-means clustering, can handle nonlinear data
pca
- 应用主成分分析将数十维数据压缩，得到主成分，根据主成分得分给案例排序，得到案例 的得分排序，从而得到评价结果。-Principal component analysis of dozens dimensional data compression, get the main ingredients, according to the principal component scores to sort the case to give the case to score the sort to
PCA-AND-PNN
- 应用主成分分析对数据降维，将得到的数据用于概率神经网络训练，进行模式识别。对于一组新数据，先计算主成分得分，再输入训练好的概率神经网络，就会得到识别结果，即改组数据属于何种类别。-Principal component analysis of the data reduction, data will be obtained for the probabilistic neural network training, pattern recognition. For a new set of d
pca_exercise
- 这是一份介绍PCA在图像处理里面的例子，里面代码都有详细介绍，很有价值-This is a descr iption of the image processing inside PCA example, which codes are detailed, great value
My_Kmeans
- java写的k-means，随机选择聚类中心-the realizationg of K-means clustering algotithm based on Java,with random selection of clustering centers