搜索资源列表
ISODATA_IRIS
- ISODATA法分类IRIS数据集,压缩包中包括两个.m文件,运行provaisodata_4D.m可直接分类。或者通过isodata_4D.m设置参数也可以得到结果。程序有详细注释,很容易懂。最后结果既有文字描述,也有图形输出。-ISODATA classification method IRIS data set, compressed package includes two. M files, run provaisodata_4D.m direct classification. Or
my_lssvm1
- 基于台湾大学林智仁教授开发的LSSVM工具箱编写的鸢尾属植物分类程序,基于四个特征中的后两个进行的分类,分类效果相当好!-classification for iris data using lssvm
PCA
- 用pca分类器将Iris数据分开,并分析pca分类器的特点-Classifier with the Iris data pca separate and analyze the characteristics of classification pca
IrisDC06
- 分类是数据挖掘 、机器学习 和模式识别 中一个重要的研究领域。分类的目的是学会一个分类模型 (称作分类器),该模型能把未知类别的数据项映射到给定类别中。目前发展较成熟的几种分类算法 如决策树、神经网络、贝叶斯方法、遗传算法等。分类具有广泛的应用,例如医学诊断、信用卡系统的信用分级、图像模式识别等。本毕业设计通过使用鸢尾属植物(IRIS)数据集,对当前数据挖掘中具有代表性的优秀分类算法进行分析和比较,总结出了各种算法的特性,为使用者选择算法或研究者改进算法提供了依据。-Classificatio
N-NSA
- 采用经典的阴性选择算法N-NSA,用IRIS数据集对算法进行耐受和检测,检测器半径固定不变,检测效率不高,因此需要采用变半径的方法检测-The negative selection algorithm using the classical N-NSA, with the IRIS data set of algorithms for tolerance and detection, the detector radius is fixed, detection efficiency is no
K近邻法
- K近邻法对Iris数据分类,输入分类结果和准确率。-K-nearest neighbor method for Iris data classification, enter the classification results and accuracy.
C
- 用C均值聚类对Iris数据分类,输出分类结果和准确度-With the C-means clustering on the Iris data classification, and accuracy of output classification results
Graphics-using-SAS-iml
- Graphics using SAS/IML: Fisher’s Iris Data This code generate 4 scatter plots and prints them on a single page. Scatter plots of sepal length versus petal length, sepal width versus petal width, sepal length versus sepal width, and petal length ver
iris
- 数据挖掘经典数据,鸢尾花分类,txt形式矩阵,直接使用非常方便。-Classical data mining data, iris classification, the form of TXT matrix directly, very convenient to use.
PCA1
- 基于PCA的iris数据集分类,matlab实现,大家共同学习。-Iris data set the PCA-based classification, the Matlab implementation, we learn together.
LDAiris
- 基于LDA的iris数据集分类算法,matlab实现,有注释。-LDA-based classification algorithm of the iris data set, the Matlab implementation, and comment.
ganzhiqi_g7
- 基于感知器的iris数据集分类算法,matlab实现,有注释。-Classification algorithm based on the iris data set of the perceptron, the Matlab implementation, and comment.
IOS
- 基于IOS自组织分析法的iris数据集分类,matlab实现,含注释。-The iris data set classification based IOS self-organization analysis, Matlab implementation, including annotations.
Kmeans
- 用matlab编写的K均值算法,测试数据为Iris数据,经调试运行良好!实验结果稳定!-K-means algorithm using matlab, test data for the Iris data, through debugging and running! Stability of the experimental results.
c
- 用C-均值聚类的方法对Iris数据进行聚类分析-Cluster analysis using C-means clustering method on the Iris data
demospp
- in this program I have simulated SPP method for iris data.
mda
- in this program, I have reduced dimension of iris data with MDA
pca
- in this program I have deduced dimension of iris data with PCA
demogsrp
- in this program I have simulated GSRP method for reducing dimension of iris data.
k_means
- k-means算法 Iris.data数据集上的实验-experiments on the k-means algorithm Iris.data data sets