资源列表
Neural-network-kalman-filter-
- 自己写的改进的BP神经网络辅助组合导航卡尔曼滤波，运行成功，可供参考。-Write their own improved BP neural network aided integrated navigation kalman filter, run successfully, for reference.
code_1
- 在机器学习中利用欧氏距离设计一个KNN分类器，实现五折交叉验证，并用PCA进行降维-Develop a k-NN classifier with Euclidean distance and simple voting.Perform 5-fold cross validation, find out which k performs the best (in terms of accuracy)。Use PCA to reduce the dimensionality to 6, then p
code_3
- 根据用户的电影收视率来预测用户的性别和年龄并且使用10折交叉验证。-predict the gender and age of users based on their ratings on movies.perform 10-fold cross validation. In each fold, users.datx(x=0,…,9) is used for test, and all other users. datxare used for training. You can use m
MPGA
- MPGA 算法 用来解决多目标工程最优化问题 亲测程序运行完美 希望可以帮到你-MPGA algorithm for solving multi-objective optimizaion problem pro-test engineering program run perfectly hope you can helpt
GsTL-1.2.1
- GsTL是一个c++库,提供了一组全面的工具和地质统计学的算法。提供的算法包括克里格、cokriging序贯仿真和p-field模拟。-GsTL is a C++ library that provides a comprehensive set of tools and algorithms for geostatistics. The algorithms provided include kriging, cokriging, sequential simulation and p-fie
CNNSVM-master
- 先利用卷及神经网络提取数据特征，再加svm进行分类-The first use of volume and neural network feature extraction data, together with the classification svm
starter
- 基于深度学习的稀疏自编码器，对图像特征进行提取，然后分类-Extraction the encoder based on sparse feature depth study
tsp
- 可视化的旅行商解决方法，C源代码，包含可执行程序，亲测可行-TSP problem
Lenet5_EasyPR_D
- 基于网上的matlab版lenet5,改成识别车牌字符，仅仅识别英文字符和数字。收集图片功能，训练，识别功能。-Based on the online version of matlab lenet5, changed license plate character recognition, identifies only English characters and numbers. Collection picture function, training and recognition.
RBFyuce.m
- 一个rbf神经网络的预测模型的matlab程序源代码-A predictive neural network model rbf
libsvm-3.21
- 此代码是林教授开发的支持向量机的源代码，需要编译器进行编译，才能采用matlab使用。-This code is developed by Professor Lin support vector machine source code, the compiler needs to compile, in order to use the MATLAB to use.
CS_SVM
- 我们使用布谷鸟智能算法优化SVM的参数（c,g）以此提高SVM的预测能力。-We use the cuckoo intelligent algorithm to optimize the parameters of the SVM (c, g) in order to improve the prediction ability of SVM.