各位知乎儿大家好,这是<EYD与机器学习>专栏读书笔记系列的第十五篇文章,这篇文章以《Hands-on Machine Learning with Scikit-Learn and TensorFlow》(后面简称为HMLST)第十五章的内容为主线,其间也会加入我们成员的一些感受和想法与大家分享。 第十五章:Autoencoders 本次的文章为大家介绍的是自编码器(Auto
\log\frac{q_\phi(\mathbf{z} \vert \mathbf{x})}{p_\theta(\mathbf{z}, \mathbf{x})} d\mathbf{z} & \scriptstyle{\text{; Because }\int q(z \vert x) dz = 1}\\ &=\underset{(\theta, \phi) \in G \times H}{\arg \min }\log p_\theta(\mathbf{x}) + \int q_\phi(\...
Minority classMajority classSynthetic samples creationSMOTEThis paper reports a new method (simplified as AE-ELM-SynMin) to create the Synthetic Minority class samples for imbalanced classification based on AutoEncoder Extreme Learning Machine (AE-ELM). AE-ELM-SynMin first trains an AE-ELM which ...
data=get_data()scaler=MinMaxScaler()dataset=scaler.fit_transform(data[['Total']])dataset=torch.tensor(dataset,dtype=torch.float32).to(device)model=AE(72).to(device)criterion=nn.MSELoss()optimizer=optim.Adam(model.parameters(),lr=1e-3)foreinrange(200):fordindataset:out,feature=model(d)loss...
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, which is usually challenging for online learning from a massive stream of data. In this paper, we propose an incremental...
数据集 Credit Card Fraud Detection 由比利时布鲁塞尔自由大学(ULB) - Worldline and the Machine Learning Group 提供。可从Kaggle上下载:https://www.kaggle.com/mlg-ulb/creditcardfraud 不想自己下载数据的,后台回复【信用卡欺诈】领取。 3、模型搭建 ...
Building an Autoencoder in Keras Keras is a powerful tool for building machine and deep learning models because it’s simple and abstracted, so in little code you can achieve great results. Keras has three ways for building a model:
It is noted that the hidden representations produced by the encoder can be used as the input for other machine learning methods, helping to initialize a network. In addition, autoencoders are often used to compress the input data, which is also known as dimension reduction, through restricting...
Nature Machine Intelligence thanks Xiuwei Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Sup...
model=VAE(input_dim,hidden_dim,latent_dim).cuda()criterion=nn.BCELoss()optimizer=optim.Adam(model.parameters(),lr=learning_rate)# 训练VAE模型forepochinrange(num_epochs):fori,(data,_)inenumerate(train_loader):data=data.cuda()data=data.view(-1,input_dim)optimizer.zero_grad()output,mu,log...