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

基于tensorflow的点击率（ctr）预测模型，易于使用，模块化，可扩展。

deepctr的Python项目详细描述

深度中心

deep ctr是一个易于使用、模块化和可扩展的基于深度学习的ctr模型包，以及许多核心组件层，可用于轻松构建自己的自定义模型。它由tensorflow实现。您可以使用任何具有model.fit()和model.predict()的复杂模型。

让我们Get Started!（Chinese Introduction）

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
NFFM	[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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