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qpso-svm
- 本程序用量子行为的粒子群算法训练支持向量机，并用IRIS数据验证了该方法的有效性
characteristicchooses
- 对给定的iris数据进行特征提取，用vc编程。
fcmgrnn
- 将FCM与广义回归网络结合起来实现对iris数据的分类-The FCM and generalized regression networks to achieve the classification of iris data
code
- 代码是MATLAB环境下基于k-nn算法的分类器对数据iris的分析-under matlab environment based on k-nn classifier for the iris.data
Bayes-Iris
- 根据贝叶斯原理设计的一个简单的分类器，利用已知样本数据训练后，分类器就可以对未知样本进行分类。（实验时采用的是Iris数据集。）-According to the design of a simple Bayesian classifier, using the known training sample data, the classifier can classify the unknown samples. (Experiments using the Iris data set.)
BP_iris
- 应用bp网络对iris数据进行分类，得到了比较准确的结果-Application bp iris data classification network, get more accurate results
Cluster
- 对iris数据进行聚类，能够得到每类的具体数据信息-Clustering of iris data, can be specific for each type of data
IRIS-use-RFclassification
- 用随机森林RF方法分类IRIS数据集，用一百个数据做训练集，五十个作为测试集，并统计出错误率，可直接运行-Classification method with random forests RF IRIS data set, using one hundred data to do training set, and fifty as a test set, and the statistical error rate, can be directly run
MSE_Iris
- mse,Iris数据集，最小平方误差判别分类器-mse, Iris data collection, the least square error determination classifier
k-means-iris
- 运用k-means算法对IRIS数据集进行聚类分析-K-means algorithm is appliled to do cluster analysis for IRIS dataset.
classification
- Iris数据的最近邻分类与k近邻分类程序，以及5路交叉验证，适合于新手学习，附有数据集-And nearest neighbor classification k-nearest neighbor classification procedure Iris data, as well as 5-way cross-validation, suitable for novices to learn, with data collection