资源列表
UJFTXJ
- 本算法采用相似搜索,和线性加权回归算法,主要用于预测,而且效果好,()
神经网络
- 传统的TSP问题，用hopfeild神经网络简单解决(The traditional TSP problem is solved by Hopfeild neural network.)
ChenxingMaterials
- 这是一种用于人类微生物疾病关联预测(Katzhmda)的katz度量的新的计算模型。(This is a novel computational model of KATZ measure for Human MicrobeDisease Association prediction)
NB
- 编写朴素贝叶斯分类器，对测试集进行分类预测，并计算分类精度(The naive Bias classifier is compiled, and the test set is classified and predicted, and the classification accuracy is calculated)
pytorch-vae-master
- 变分子编码 重构图像 Mnist 特征提取(vae reconstruction Mnist feature extracting)
qlearning4k-master
- qlearning4k是强化学习Python深度学习lib库Keras插件。它简单，是快速成型的理想选择。(Qlearning4k is a reinforcement learning add-on for the python deep learning library Keras. Its simple, and is ideal for rapid prototyping.)
deep_q_rl-master
- This package provides a Lasagne/Theano-based implementation of the deep Q-learning algorithm described in: Playing Atari with Deep Reinforcement Learning Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierst
DeepLearnToolbox_CNN_lzbV3.0
- cnn的MATLAB编程语言可以进行学习深度学习的编程语言与基础应用(Cnn's MATLAB programming language)
BP_annotate
- 模拟仿真 ，神经网络训练，BP神经网络算法及建立(simulink,train,BP net work)
KNN分类器
- 一、用python或matlab编写一个KNN分类器 训练集为semeion_train.csv（手写体识别） 测试集为semeion_test.csv 计算在测试集上错误率（k=1,k=3,k=5,k=10） ?(1. Write a KNN classifier with Python or matlab Training set is semeion_train.csv (handwriting recognition) The test set is semeion_test
libsvm-3.22
- Matlab中的一个工具箱,可以用来分类(a toolbox in Matlab,it can be used to classify data.)
htru2
- 对脉冲星的二分类问题，利用逻辑回归，里面有详细的注解(For the two classification problem of pulsars, there are detailed annotations.)