pykeen
v1.8.2
Getting Started
Installation
First Steps
Tracking Results during Training
Saving Checkpoints during Training
A Toy Example with Translational Distance Models
Understanding the Evaluation
Optimizing a Model’s Hyper-parameters
Novel Link Prediction
Running an Ablation Study
Performance Tricks
Representations
Getting Started with NodePiece
Inductive Link Prediction
PyTorch Lightning Integration
Bring Your Own
Bring Your Own Data
Bring Your Own Interaction
Extending PyKEEN
Extending the Datasets
Extending the Models
Extending the Interaction Models (Old-Style)
Reference
Pipeline
Functions
pipeline_from_path
pipeline_from_config
replicate_pipeline_from_config
replicate_pipeline_from_path
pipeline
plot_losses
plot_early_stopping
plot_er
plot
Classes
Models
Datasets
Inductive Datasets
Entity Alignment
Triples
Training
Stoppers
Loss Functions
Regularizers
Result Trackers
Negative Sampling
Filtering
Evaluation
Metrics
Hyper-parameter Optimization
Ablation
Lookup
Prediction
Uncertainty
Sealant
Constants
pykeen.nn
Utilities
Appendix
References
pykeen
»
Pipeline
»
plot
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plot
plot
(
pipeline_result
,
er_kwargs
=
None
,
figsize
=
(10,
4)
)
[source]
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v: v1.8.2
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