Python easymatch包_程序模块 - PyPI - Python中文网

轻松匹配

easymatch的Python项目详细描述

DeepCTR公司

DeepCTR是一个易于使用的，模块化和可扩展的软件包，包括基于深度学习的CTR模型以及许多可用于轻松构建定制的核心组件层模型。它与tensorflow 1.4+和2.0+兼容。您可以使用model.fit()和model.predict()。在

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型号列表

Model	Paper
Convolutional Click Prediction Model	[CIKM 2015]A Convolutional Click Prediction Model
Factorization-supported Neural Network	[ECIR 2016]Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction
Product-based Neural Network	[ICDM 2016]Product-based neural networks for user response prediction
Wide & Deep	[DLRS 2016]Wide & Deep Learning for Recommender Systems
DeepFM	[IJCAI 2017]DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
Piece-wise Linear Model	[arxiv 2017]Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction
Deep & Cross Network	[ADKDD 2017]Deep & Cross Network for Ad Click Predictions
Attentional Factorization Machine	[IJCAI 2017]Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
Neural Factorization Machine	[SIGIR 2017]Neural Factorization Machines for Sparse Predictive Analytics
xDeepFM	[KDD 2018]xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems
AutoInt	[arxiv 2018]AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
Deep Interest Network	[KDD 2018]Deep Interest Network for Click-Through Rate Prediction
Deep Interest Evolution Network	[AAAI 2019]Deep Interest Evolution Network for Click-Through Rate Prediction
ONN	[arxiv 2019]Operation-aware Neural Networks for User Response Prediction
FGCNN	[WWW 2019]Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction
Deep Session Interest Network	[IJCAI 2019]Deep Session Interest Network for Click-Through Rate Prediction
FiBiNET	[RecSys 2019]FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction

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