资源列表
maze_TD_lamda
- 时序差分学习算法TD(lamda)求解N*N方格走迷宫问题，求解每个方格的V值-Temporal difference learning algorithm for N*N maze problem
BP
- 三层神经网络算法，不适用MATLAB的库函数，自带数据集，测试通过-Three-layer neural network algorithm, does not apply MATLAB library functions, comes with data sets, tested
svm
- 基于matlab用支持向量机实现分类决策 -Based on matlab support vector machine to classify Decision
xm_LeakMax_MainProg
- 多态系统的贝叶斯网络模型的参数学习算法，基于Noisy-Max模型-Parameters Learning of Bayesian Networks for Multistate System，based Noisy-MAX model
xm_LeakMax_MainProg_Alarm
- BN网络建模，Alarm标准案例中的节点参数学习算法，基于Noisy-Max模型-Based Noisy-Max model，Parameters Learning of Bayesian Networks for Alarm Case
xm_LeakMax_MainProg_Hepar
- 基于因果独立模型的Hepar网络参数学习算法，Hepar网络是BN学习中常用的标准案例-Parameters Learning of Bayesian Networks Based on Independence of Causal Influence Model for Hepar Case
xm_CPTDistanceCompare
- BN网络参数之间的KL距离 (Kullback–Leibler Distance) 计算，用于比较相似度-BN KL distance between network parameters calculation, used to compare similarity
xm_SimulateSamples_fromBNT
- 根据贝叶斯网络结构bnt，随机产生nsamples条样本集，样本集的数据缺失率为miss_perc-BNT based on bayesian network structure, random generation nsamples sample set, data loss rate is miss_perc sample set
1-s2.0-S0925231213009909-main
- 一种改进型的新型极限学习机meta-elm,在训练效率上有很大提升-meta extrem learning machine
bpshigaijin
- 用matlab编程实现BP算法的改进，通过改进误差函数实现，文件包含M文件-Matlab programming with improved BP algorithm, the error function by improving the implementation of the file containing the file M
BP
- 用C语言编写的BP神经网络算法，能够实现6输入3输出的神经网络-BP neural network algorithm written in C, it is possible to achieve 3 6 input output neural network
neural-network
- 深度学习python实现，并附有MNIST上的测试程序，准确率98 以上-Deep learning learns low and high-level features large amounts of unlabeled data, improving classification on different, labeled, datasets. Deep learning can achieve an accuracy of 98 on the MNIST dataset.