Add EnsembleMF: ensembled two-tower matrix factorization

docs/drevalpy.models.EnsembleMF.rst

@@ -0,0 +1,7 @@
+EnsembleMF
+============================
+
+.. automodule:: drevalpy.models.EnsembleMF.ensemble_mf
+   :members:
+   :undoc-members:
+   :show-inheritance:

docs/drevalpy.models.rst

@@ -26,6 +26,7 @@ Implemented models
 
    drevalpy.models.DIPK
    drevalpy.models.DrugGNN
+   drevalpy.models.EnsembleMF
    drevalpy.models.MOLIR
    drevalpy.models.PharmaFormer
    drevalpy.models.Precily

docs/usage.rst

@@ -256,7 +256,7 @@ needing separate model classes. By default they use gene expression and fingerpr
 See the sklearn model :ref:`flexible-inputs` or the SimpleNeuralNetwork :ref:`flexible-inputs-simplenn` for details.
 
 +---------------------------------+----------------------------+--------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-| Model Name                      | Baseline / Published Model | Multi-Drug Model / Single-Drug Model | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
+| Model Name                      | Baseline / Published / New | Multi-Drug Model / Single-Drug Model | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
 +=================================+============================+======================================+============================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================+
 | NaivePredictor                  | Baseline Method            | Multi-Drug Model                     | Most simple method. Predicts the mean response of all drugs in the training set.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
 +---------------------------------+----------------------------+--------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
@@ -310,6 +310,8 @@ See the sklearn model :ref:`flexible-inputs` or the SimpleNeuralNetwork :ref:`fl
 +---------------------------------+----------------------------+--------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
 | Precily                         | Published Model            | Multi-Drug Model                     | `Precily <https://doi.org/10.1038/s41467-022-33291-z>`_ from Chawla et al. Uses GSVA pathway-activity scores with SMILESVec drug embeddings. Features are concatenated and passed through multiple linear layers with ReLU and Dropout.                                                                                                                                                                                                                                                                                                                                                    |
 +---------------------------------+----------------------------+--------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
+| EnsembleMF                      | New Model                  | Multi-Drug Model                     | Ensembled two-tower matrix factorization. Cell-line and drug latent factors are produced by small residual MLPs over gene expression and Morgan fingerprints, combined by a dot product with per-cell/per-drug/global biases, a free per-drug embedding and a small interaction head. Averaged over N independently seeded members.                                                                                                                                                                                                                                                        |
++---------------------------------+----------------------------+--------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
 
 
 Available Datasets

drevalpy/models/EnsembleMF/__init__.py

@@ -0,0 +1,5 @@
+"""Module for the EnsembleMF model."""
+
+__all__ = ["EnsembleMF"]
+
+from .ensemble_mf import EnsembleMF