有效样本特征的挖掘,不仅能够提升模型效果的天花板,还能够为离线链路、在线链路有效瘦身,释放系统预估能力。 一种用于深度学习的通用特征排序方法《Dropout feature ranking for deep learning models》教会了我们如何做粗排模型兼顾模型的效率和效果。 论文标题:Dropout feature ranking for deep learning models 下载地址:ht...
《Dropout Feature Ranking for Deep Learning Models》C Chang, L Rampasek, A Goldenberg [University of Toronto] (2017) http://t.cn/RHfZSb9
We aim to close this gap by proposing a new general feature ranking method for deep learning. We show that our simple yet effective method performs on par or compares favorably to eight strawman, classical and deep-learning feature ranking methods in two simulations and five very different ...
Individual dropout feature rankingDeep learningMachine learningArtificial intelligenceDeep learning is the fastest growing field in artificial intelligence and has led to many transformative innovations in various domains. However, lack of interpretability sometimes hinders its application in hypothesis-driven ...
不同于MLP的特征层是一个特征向量，CNN的Feature Map是一个由宽，高，通道数组成的三维矩阵。按照传统...
This project contains the code implemented in the paperFeature Ranking by Variational dropout for Classification Using Thermograms from Diabetic Foot Ulcers. The data presented in the work are available on request. The data are not publicly available due to privacy restrictions. ...
我猜测是为了“在 infer 时不进行dropout”。dropout是带有随机性的，如果 infer 也做的话，网络的输出...
Our process begins with data collection over 13 years, from kindergarten to the end of upper secondary education (Step 1), followed by data processing which includes cleaning and imputing missing feature values (Step 2). We then apply four machine learning models for dropout and non-dropout ...
We aim to close this gap by proposing a new general feature ranking method for deep learning. We show that our method outperforms LASSO, Elastic Net, Deep Feature Selection and various heuristics on a simulated dataset. We also compare our method in a multivariate clinical time-series dataset ...
1 dropout提出背景 深度模型的结构中，当前层神经元的输入是上一层神经元的输出，神经元的相互依赖使...