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chapter28
- 支持向量机的分类——基于乳腺组织电阻抗特性的乳腺癌诊断-Support Vector Machine- based breast tissue electrical impedance characteristics of breast cancer diagnosis
GRNN_PNN
- 将训练集与测试集数据进行归一化； 建立GRNN或PNN神经网络； 利用建立好的神经网络对测试集中的26个乳腺组织样本的类型进行预测； 计算预测正确率（不必计算每类的正确率，只需计算正常或者病变两类的正确率，即只要预测结果与真实值属于同一大类，则认为是正确，否则认为预测错误）-The training set and test data set is normalized Establish GRNN or PNN neural network The use of wel
Breast-MRI
- 这是一组实验用的乳腺磁共振图像实测数据，可用于医学图像处理-This is a group of breast MRI experiment measured data can be used for medical image processing
UCIdata
- 神经网络的应用——分类器中常用的分类数据集：乳腺肿瘤识别-That is commonly used in the application of neural network, a classifier classification data sets: breast tumor recognition
main
- chapter28支持向量机的分类——基于乳腺组织电阻抗特性的乳腺癌诊断(Classification of chapter28 support vector machines - breast cancer diagnosis based on breast tissue impedance)
random forest
- 此源程序包含随机森林工具箱，以及将随机森林算法用于乳腺肿瘤数据的分类预测(This source includes random forest toolbox, and random forest algorithm is used to classify and predict breast tumor data.)
乳腺肿瘤自动分割程序
- 基于CV模型的自动分割,能够对灰度图分割操作(image segmentation Level set Chan-Vase)