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psoyouhuannyj
- 基于粒子群优化的神经网络训练算法研究论文 摘 要: 本文提出了基于连接结构优化的粒子群优化算法(SPSO) 用于神经网络训练,该算法在训练神经网络权 值的同时优化其连接结构,删除冗余连接,使神经网络获得与模式分类问题匹配的信息处理能力. 经SPSO 训练的神经 网络应用于Iris ,Ionosphere 以及Breast cancer 模式分类问题,能够部分消除冗余分类参数及冗余连接结构对分类性能 的影响. 与BP 算法及遗传算法比较,该算法在提高分类误差精度的同时可加快训
f_CIN-2-Bhanot-et-al_163
- Data Perturbation Independent Diagnosis and Validation of Breast Cancer Subtypes Using Clustering and Patterns
BP-neural-network
- BP神经网络 乳腺癌诊断 自动选择最佳神经元个数-BP neural network automatically select the best breast cancer diagnosis the number of neurons
LVQ
- LVQ神经网络的分类——乳腺肿瘤诊断-LVQ neural network classification- breast cancer diagnosis
breast-cancer-imaging-with-a-variabel-field-of-vi
- Medical Image Fusion in breast cancer.
breast-cancer
- 用ISOMAP算法对癌症数据进行降维处理，然后再对降维后的数据进行可视化分析-ISOMAP algorithm to reduce the dimensionality of cancer data processing, data dimensionality reduction and then to visualization analysis
svm-Diagnosis-of-breast-cancer
- 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 classification- based on electrical impedance characteristics of breast tissue diagnosis of breast cancer
breast-tumor-diagnosis-based-on-BP
- LVQ神经网络的分类——乳腺肿瘤诊断相关程序-The classification of LVQ neural network- breast cancer diagnosis relative program
Mammogram-breast-cancer-image-detection
- Mammogram breast cancer image detection MATLAB File
breast-segmentation
- breast cancer detection
MATLAB-breast-cancer-detection
- breast cancer detection matlab- breast cancer detection matlab
[3]pawar2016
- Genetic Fuzzy System (GFS) based Wavelet Co-occurrence Feature selection in Mammogram Classification for Breast Cancer Diagnosis
breast-cancer-wisconsin.data
- 分类数据集，一般用于机器学习，数据挖掘等(breast;cancer;wisconsin;data)
Classification
- Breast cancer diagnsis
Segmentation
- Breast cancer segmentation
Breast cancer
- diagnosis from images
CD6712
- Breast cancer diagnosis
DESIGN
- DESIGN OF A Breast cancer diagnosis
calcularGanancia
- It implements genetic algorithm in diagnosing breast cancer.
som_breast
- It diagnoses the breast cancer using som algorithm.