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DeepPatientLevelPrediction
2.0.3
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My first deep learning model
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Building Deep Learning Models
Developing your first DeepPLP model
DeepPatientLevelPrediction Installation Guide
Changelog
Changelog
Source:
NEWS.md
DeepPatientLevelPrediction 2.0.3
Hotfix: Fix count for polars v0.20.x
DeepPatientLevelPrediction 2.0.2
Ensure output from predict_proba is numeric instead of 1d array
Refactoring: Move cross-validation to a separate function
Refactoring: Move paramsToTune to a separate function
linting: Enforcing HADES style
Calculate AUC ourselves with torch, get rid of scikit-learn dependancy
added Andromeda to dev dependencies
DeepPatientLevelPrediction 2.0.1
Connection parameter fixed to be in line with newest polars
Fixed a bug where LRFinder used a hardcoded batch size
Seed is now used in LRFinder so it’s reproducible
Fixed a bug in NumericalEmbedding
Fixed a bug for Transformer and numerical features
Fixed a bug when resuming from a full TrainingCache (thanks Zoey Jiang and Linying Zhang )
Updated installation documentation after feedback from HADES hackathon
Fixed a bug where order of numeric features wasn’t conserved between training and test set
TrainingCache now only saves prediction dataframe for the best performing model
DeepPatientLevelPrediction 2.0.0
New backend which uses pytorch through reticulate instead of torch in R
All models ported over to python
Dataset class now in python
Estimator class in python
Learning rate finder in python
Added input checks and tests for wrong inputs
Training-cache for single hyperparameter combination added
Fixed empty test for training-cache
DeepPatientLevelPrediction 1.1.6
Caching and resuming of hyperparameter iterations
DeepPatientLevelPrediction 1.1.5
Fix bug where device function was not working for LRFinder
DeepPatientLevelPrediction 1.1.4
Remove torchopt dependancy since adamw is now in torch
Update torch dependency to >=0.10.0
Allow device to be a function that resolves during Estimator initialization
DeepPatientLevelPrediction 1.1.3
Fix actions after torch updated to v0.10 (
#65
)
DeepPatientLevelPrediction 1.1.2
Fix bug introduced by removing modelType from attributes (
#59
)
DeepPatientLevelPrediction 1.1
Check for if number of heads is compatible with embedding dimension fixed (
#55
)
Now transformer width can be specified as a ratio of the embedding dimensions (dimToken), (
#53
)
A custom metric can now be defined for earlyStopping and learning rate schedule (
#51
)
Added a setEstimator function to configure the estimator (
#51
)
Seed added for model weight initialization to improve reproducibility (
#51
)
Added a learning rate finder for automatic calculatio of learning rate (
#51
)
Add seed for sampling hyperparameters (
#50
)
used vectorised torch operations to speed up data conversion in torch dataset
DeepPatientLevelPrediction 1.0.2
Fix torch binaries issue when running tests from other github actions
Fix link on website
Fix tidyselect to silence warnings.
DeepPatientLevelPrediction 1.0.1
Added changelog to website
Added a first model tutorial
Fixed small bug in default ResNet and Transformer
DeepPatientLevelPrediction 1.0.0
created an Estimator R6 class to handle the model fitting
Added three non-temporal models. An MLP, a ResNet and a Transformer
ResNet and Transformer have default versions of hyperparameters
Created tests and documentation for the package
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