搜索资源列表
FCM
- 核聚类算法：聚类是将一组给定的未知类标号的样本分成内在的多个类别，使得同一类中 的样本具有较高的相似度，而不同类中的样本差别大。侧重于软聚类（模糊C-均值——FCM），但其描述手段同样适合于硬聚 类（HCM）等同类问题。-Clustering algorithm: cluster is a group of unknown samples given class label into internal multiple categories, so that the same class
xitongbianshi
- 最小二乘法系统辨识 包括基本最下二乘、递推最小二乘、广义、增光最小二乘等等。-Least squares identification system including basic two multiplication, recursive least squares, generalized least squares, credit and so on.
rw
- 最大熵随机游走，在每一步中令熵率保持局部最大-The maximum entropy random walk, so entropy rate at each step to keep the local maximum
zishiyingguolvfa
- 自适应过滤法是根据一组给定的权数对时间数列的历史观察值进行加权平均计算一个预测值，然后根据预测误差调整权数以减少误差，这样反复进行直至找出一组“最佳”权数，使误差减少到最低限度，再利用最佳权数进行加权平均预测。-Adaptive filtering method is based on the number of a given set of rights to compute a weighted average of the predicted value of historical tim
MC
- MC问题（AI）的解答，用JAVA实现。野人与传教士问题。（ArrayList）-The solution to MC problem which is so typical in AI field ,when it comes to the expression of knowledge.Use Java.ArrayList
EM
- 对于混合高斯分布的情况，使用最大期望算法，通过不断计算每个样本的均值与方差，使得似然函数达到最大值。可以很好地处理满足一定概率分布的数据。 代码中通过mvnrnd()函数，设定其中的参数，产生符合混合高斯分布的一组数据集。-For the case of a mixed Gaussian distribution, using expectation-maximization algorithm, through continuous calculation of the mean and
multiverso-master
- Multiverso is a parameter server based framework for training machine learning models on big data with numbers of machines. It is currently a standard C++ library and provides a series of friendly programming interfaces. With such easy-to-use APIs, m
GAKMeans
- 由于Kmeans聚类分析是一个局部的搜索过程，因此加入遗传算法进行全局搜索选择最优的初始中心点使得Kmeans算法产生较大的改进-Since Kmeans Cluster analysis is a local search process, so join a global search for the genetic algorithm to the optimal initial centers such Kmeans algorithm produces greater improve
RF
- 在机器学习中，随机森林由许多的决策树组成，因为这些决策树的形成采用了随机的方法，所以叫做随机森林。-In machine learning, Random Forests decision tree composed of many, because of the formation of these decision trees using random method, so called Random Forest.
ThemeCrawler
- 现在常见的搜索策略主要分为两种：一种是基于网页链接结构的搜索策略，另一种是基于内容评价的搜索策略。第一种是通过网页之间的链接关系来确定网页的重要性，从而决定链接访问的顺序。此方法虽然考虑了网页链接结构和网页之间的链接关系，但忽略了网页内容与主题的相关度，容易出现网页搜索“主题漂移”。第二种主要考虑网页内容，好处就是思路清晰且计算简单。但这种方法忽略了网页的链接关系，故在预测链接网页价值方面存在不足。考虑到这些问题，提出将布谷鸟搜索算法应用到主题爬虫中。-Now the common search
beautifulsoup4-4.0.0b3.tar
- Beautiful Soup提供一些简单的、python式的函数用来处理导航、搜索、修改分析树等功能。-Beautiful Soup offers some simple, python-like functions to handle navigation, search, modify the parse tree and so on.
prog-hive-1st-ed-data
- Hive编程指南源代码，里面含有数据源，例如股票的信息。因为自己平时也要用积分下载资源，所以设置了一分。-Hive Programming Guide source code, which contains the data source, such as stock information. Because they usually have to use points to download resources, so we set up a point.
E-Algorithm
- 用于数据挖掘分类的算法，E-Alothm，并附有10个左右的KEEL专用数据集，算法实现+实际例程。-For the data mining classification algorithm, E-Alothm, and with 10 or so KEEL dedicated data set, the algorithm to achieve+ practical routines.
GetMP4ba
- 前两天看到MP4ba竟然加入了各种广告！！！故写了此爬虫来爬取所有的电影磁力链接。 可以爬取所有mp4ba的磁力链接喔(Two days ago, I saw MP4ba join all kinds of ads!!! So I wrote this crawler to climb up all the movie magnetic links. You can climb up all of mp4ba's magnetic links)
code
- ssmfa将高光谱数据从高维观测空间投影到低维流形空间，达到约减数据维数的目的(ssmfa hyperspectral data is projected from the high dimensional observation space into the low dimensional manifold space, so as to reduce the dimensionality of data)
kmeans
- 对数据和图像进行聚类分析，k-means聚类方法多应用于模式识别，人工智能，机器学习等方面(Clustering analysis of data and images, K-means clustering method should be used in pattern recognition, artificial intelligence, machine learning and so on)
EM 算法
- 用EM算法求解高斯混合模型并可视化，数据是男女生的身高分布，前提是初始化男女生身高各自的均值和方差和比例，然后由EM算法求解，男女生身高的均值方差，以拟合数据。(The EM algorithm is used to solve the Gauss mixture model and visualize. The data is the height distribution of male and female. The premise is to initialize the mean, v