Elliot
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Introduction
Install Elliot
Quick Start
Release Notes
RUNNING EXPERIMENTS
Configuration file
Data Preparation
ALGORITHMS
Summary of the Recommendation Algorithms
Hyperparameter Optimization
Early Stopping
Create a new Recommendation Model
Recommendation Models
Adversarial Learning
Algebric
Autoencoders
Content-Based
Generative Adversarial Networks (GANs)
Graph-based
Knowledge-aware
Latent Factor Models
Artificial Neural Networks
Neighborhood-based Models
Unpersonalized Recommenders
Visual Models
EXTENDING ELLIOT
Loaders
Recommendation Models
Adversarial Learning
Algebric
Autoencoders
Content-Based
Generative Adversarial Networks (GANs)
Graph-based
Knowledge-aware
Latent Factor Models
Artificial Neural Networks
Neighborhood-based Models
Unpersonalized Recommenders
Visual Models
EVALUATION
Metrics
Metrics Summary
Evaluation of recommendation files
API REFERENCE
elliot package
elliot.dataset package
elliot.evaluation package
elliot.namespace package
elliot.hyperoptimization package
elliot.prefiltering package
elliot.recommender package
elliot.result_handler package
elliot.splitter package
elliot.utils package
Elliot
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Recommendation Models
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Recommendation Models
¶
Adversarial Learning
Algebric
Autoencoders
Content-Based
Generative Adversarial Networks (GANs)
Graph-based
Knowledge-aware
Latent Factor Models
Artificial Neural Networks
Neighborhood-based Models
Unpersonalized Recommenders
Visual Models
Read the Docs
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