搜索资源列表
ANN_BP--classifier
- ANNbp对UCI中鸢尾花数据集分类,150做训练样本,剩下150做测试样本-ANNbp on the UCI iris data set classification, 150 training samples, the remaining 150 test samples
Parallel-axis
- 平行坐标轴是可视化的一种传统方法,用于模式识别聚类等,数据是‘鸢尾花数据集’,有较好的分类效果。-Parallel to the axis is a traditional way to visualize, used for clustering and pattern recognition, data is the iris data set, have better classification effect.
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)
iris
- 使用iris鸢尾花数据集测试rbf神经网络的分类效果(Using iris iris dataset to test the classification effect of RBF neural network)
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.)
鸢尾花
- 封装KNN算法,了解IRIS数据集 分类鸢尾花数据集(Encapsulation of KNN algorithm to understand IRIS dataset classification iris dataset)
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)
Fishr集-鸢尾花分类源程序和相关文件
- IRIS SVM分类 初尝试 自带数据集(IRIS SVM CLASSIFICATION)