%目标函数值的计算 fit(i)=fitness( Positions(i,:)); % 更新领导者位置 if fit(i)<Leader_score Leader_score=fit(i); Leader_pos=Positions(i,:); end end a=2-t*((2)/maxgen); a2=-1+t*((-1)/maxgen); %参数更新 for i=1:size(Positions,1
cf_ = fit(X(ok_),Y(ok_),ft_); 修改为: [cf_,gof] = fit(X(ok_),Y(ok_),ft_); 1. 2. 3. 然后将函数声明 function createFit(X,Y) 修改为 function [cf_,gof] = createFit(X,Y) ,这样我们再调用试试看: Y=[12 15 4 1 7 11 5 7 1 6 16 1 1 14 2 12 9 13 10 12 ...
%目标函数值的计算 fit(i)=fitness( Positions(i,:)); % 更新领导者位置 if fit(i)<Leader_score Leader_score=fit(i); Leader_pos=Positions(i,:); end end a=2-t*((2)/maxgen); a2=-1+t*((-1)/maxgen); %参数更新 for i=1:size(Positions,1) r1=rand();r2=rand(); A=2*a*r1-a...
(n_components=2, learning_rate='auto',init='random').fit_transform(x_inter) # Get the true labels for every data point in the training set y_label = enc.inverse_transform(y_train).reshape(-1) # Create a scatter plot of the embedded data, colored by the true labels f, ax = plt...
基于脉冲小波的旋转机械故障诊断(MATLAB R2018a) 完整代码可通过知乎付费咨询获得: https://www.zhihu.com/consult/people/792359672131756032 Python环境下基于机器学习和深度学习的轴承故障诊断方法 程序运行环境为Python,采用tensorflow,keras和sklearn等模块,执行基于机器学习和深度学习模型的轴承故障诊断。主要内容包括: ...
trainNow = ; if trainNow % Since the size of the training data set is very large, it cannot all % fit into the memory. Set up a signalDatastore object that can % efficiently load only that portion of the data set that is required % for training at a current iteration. waveformDatast...
Training a deep learning model usually requires many training observations to achieve a good fit. When you do not have much training data available, you can try to improve the fit of the network by artificially increasing the size of the training data using augmentations. Create an audioDataAug...
1. 同一般机器学习算法,先定义Loss function,衡量和实际结果之间差距。 2. 找到最小化损失函数的W和b, CNN中用的算法是SGD(随机梯度下降)。 卷积神经网络之优缺点 优点 • 共享卷积核,对高维数据处理无压力 • 无需手动选取特征,训练好权重,即得特征分类效果好 ...
To assess the efficacy of a rolling-window analysis, we began by building a CNN classification scheme based on a modified version of Google’s Inception V338(see Methods). The first and last layers of the model were altered to fit our preprocessed image size of\(320 \times 180\)pixels wi...
makedirs(log_dir)#input image dimensionsimg_rows, img_cols = 1, 2048'''第一步 准备数据'''#matlab文件名 准备数据file_name = u'G:/GANCode/CSWU/12k drive end vps/trainset/D/D_dataset.mat'original_data=sio.loadmat(file_name)