搜索资源列表
fisher判别分析
- 利用fisher判别分析对于鸢尾花数据集进行分类(Fisher discriminant analysis was used to classify iris data sets)
shiyan4
- 解决非线性多类别分类问题,利用实际数据进行分类处理。(Solving nonlinear multi class classification problem, using actual data for classification processing.)
BP Matlab实现
- 采用Iris数据集在matlab上实现简单的数据训练和分类(Using Iris data set in matlab to achieve a simple data training and classification.)
irisdatasetclustering
- IRIS DATA SET CLUSTERING IN MATLAB
bp神经网络
- 在matalab上利用bp神经网络对iris 数据进行分类(iris data mashine learning)
Matlab_SVM
- SVM算法实现+数据 (要用到一些包,按照代码里面的import到网站下就行) 1.读取数据:在Matlab中调用textread可读取UCI数据集,这里读取的文件是iris.data,因为文件中以逗号为分隔符,所以还要在读取方法中添加参数“‘delimiter’,‘,’”,从而在读数据的时候自动跳过分隔符。 2.调用cvx工具箱中的方法:首先需要下载cvx工具箱的压缩文件,在其目录下运行cvx_setup指令,然后调用其方法,以cvx_begin开头,cvx_end为终止符号,所有需
模式识别实验一
- matlab,模式识别,基于Iris数据设计编写两类正态分布模式的贝叶斯判别程序(Pattern recognition report, based on Iris data design, two kinds of Bayesian discriminant program for normal distribution mode are written.)
nyc_weather
- NYC Weather Data NYC include TMAX, TMIN, Wind AVG, PRCP
MATLAB实现鸢尾花数据集分类
- 基于BP算法的鸢尾花数据集分类,在MATLAB平台下编程实现BP算法,可计算识别率。(Based on the BP algorithm, iris data set is classified. Under the MATLAB platform, the BP algorithm is programmed and the recognition rate can be calculated.)
irisdata
- 用于聚类的数据集。。。。。。。。。。。。。(Data sets for clustering)
分类器评估及交叉验证_代码
- 内有鸢尾花数据的5折交叉验证实验代码,采用的分类器是贝叶斯分类器。(There is a 5-fold cross-validation experiment code for the iris data, and the classifier used is a Bayesian classifier.)
Random_Forest
- 内涵PCA降维;SMOTE插值;t-SNE降维等算法的随机森林算法,以及鸢尾花数据集,有利于新手或者工程性实验借鉴~(Connotative PCA dimensionality reduction; SMOTE interpolation; t-SNE dimensionality reduction algorithms such as random forest algorithm, as well as iris data sets, is conducive to novice or
SVM_tensorflow-master
- SVM通过tensorflow训练iris数据集,寻找最优参数,使误差最小化(SVM trains iris data set through tensorflow to find the optimal parameters and minimize the error.)
iris_data
- Iris Data Set(鸢尾属植物数据集)是我现在接触到的历史最悠久的数据集,它首次出现在著名的英国统计学家和生物学家Ronald Fisher 1936年的论文《The use of multiple measurements in taxonomic problems》中,被用来介绍线性判别式分析。在这个数据集中,包括了三类不同的鸢尾属植物:Iris Setosa,Iris Versicolour,Iris Virginica。每类收集了50个样本,因此这个数据集一共包含了150个样本。
量子行为的粒子群算法-SVM
- 改进量子粒子群算法,用于优化支持向量机参数,用IRIS数据验证(An improved quantum particle swarm optimization (QPSO) algorithm is used to optimize the parameters of support vector machine (SVM), which is validated by IRIS data.)
k-means-for-iris
- 利用K均值聚类对鸢尾花样本进行聚类的matlab程序,包含源代码、样本数据、聚类结果(The matlab program of clustering iris samples by K-means clustering, including source code, sample data and clustering results)
can_use_kmeans
- K-means对iris数据集进行分类,可画出3维分类图(K-means to classify iris data set)
svm
- 利用支持向量机,对鸢尾花数据集进行分类。(Support vector machine is used to classify iris data set.)
svm分类鸢尾花数据集
- Three classifications of iris data using SVM based on Anaconda
鸢尾花 数据的处理
- MATLAB 利用Fisher分析和核Fisher分析对鸢尾花数据集进行分类,可以发现Kfisher 可以较好地对非线性数据的分类(MATLAB USES Fisher analysis and core Fisher analysis to classify the iris data set, and it can be found that Kfisher can classify the nonlinear data well)