Basket models

README.md

@@ -53,7 +53,7 @@ If you are new to choice modeling, you can check this [resource](https://www.pub
 
 | Dataset    | Raw Data | Origin | *from choice_learn.datasets import* | Doc |
 | ---------- | :----: | ------ | ------ | :---: |
-| SwissMetro  | [csv](./choice_learn/datasets/data/swissmetro.csv.gz)    | Bierlaire et al. (2001) [[2]](#trident-references) | *load_swissmetro* | [#](https://artefactory.github.io/choice-learn/references/datasets/references_base/#choice_learn.datasets.base.load_swissmetro) |
+| SwissMetro  | [csv](./choice_learn/datasets/data/swissmetro.csv.gz) | Bierlaire et al. (2001) [[2]](#trident-references) | *load_swissmetro* | [#](https://artefactory.github.io/choice-learn/references/datasets/references_base/#choice_learn.datasets.base.load_swissmetro) |
 | ModeCanada | [csv](./choice_learn/datasets/data/ModeCanada.csv.gz) | Forinash and Koppelman (1993) [[3]](#trident-references) | *load_modecanada* | [#](https://artefactory.github.io/choice-learn/references/datasets/references_base/#choice_learn.datasets.base.load_modecanada) |
 | Train    | [csv](./choice_learn/datasets/data/train_data.csv.gz) | Ben-Akiva et al. (1993) [[5]](#trident-references) |*load_train* | [#](https://artefactory.github.io/choice-learn/references/datasets/references_base/#choice_learn.datasets.base.load_train) |
 | Heating | [csv](./choice_learn/datasets/data/heating_data.csv.gz) | Kenneth Train's [website](https://eml.berkeley.edu/~train/) | *load_heating* | [#](https://artefactory.github.io/choice-learn/references/datasets/references_base/#choice_learn.datasets.base.load_heating) |
@@ -73,18 +73,22 @@ If you are new to choice modeling, you can check this [resource](https://www.pub
 | Model | Example | Colab | Related Paper | *from choice_learn.models import* | Doc |
 | ---------- | -------- | -------- | ------ | ------ | :---: |
 | MNL | [notebook](notebooks/models/simple_mnl.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/simple_mnl.ipynb) | | *SimpleMNL* | [#](https://artefactory.github.io/choice-learn/references/models/references_simple_mnl/) |
-| Conditional Logit  | [notebook](notebooks/introduction/3_model_clogit.ipynb)    | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/introduction/3_model_clogit.ipynb) | Train et al. [[4]](#trident-references)         | *ConditionalLogit* | [#](https://artefactory.github.io/choice-learn/references/models/references_clogit/) |
+| Conditional Logit | [notebook](notebooks/introduction/3_model_clogit.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/introduction/3_model_clogit.ipynb) | Train et al. [[4]](#trident-references)         | *ConditionalLogit* | [#](https://artefactory.github.io/choice-learn/references/models/references_clogit/) |
 | Nested Logit | [notebook](notebooks/models/nested_logit.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/nested_logit.ipynb) | McFadden [[10]](#trident-references)  | *NestedLogit* | [#](https://artefactory.github.io/choice-learn/references/models/references_nested_logit/) |
-| Latent Class MNL    | [notebook](notebooks/models/latent_class_model.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/latent_class_model.ipynb) | | *LatentClassConditionalLogit* | [#](https://artefactory.github.io/choice-learn/references/models/references_latent_class_mnl/) |
-| Halo MNL    | [notebook](notebooks/models/halo_mnl.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/halo_mnl.ipynb) | Maragheh et al. [[14]](#trident-references) | *HaloMNL* | [#](https://artefactory.github.io/choice-learn/references/models/halo_mnl/) |
-| Low-Rank Halo MNL    | [notebook](notebooks/models/halo_mnl.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/halo_mnl.ipynb) | Ko and Li [[15]](#trident-references) | *LowRankHaloMNL* | [#](https://artefactory.github.io/choice-learn/references/models/halo_mnl/) |
+| Latent Class MNL | [notebook](notebooks/models/latent_class_model.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/latent_class_model.ipynb) | | *LatentClassConditionalLogit* | [#](https://artefactory.github.io/choice-learn/references/models/references_latent_class_mnl/) |
+| Halo MNL | [notebook](notebooks/models/halo_mnl.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/halo_mnl.ipynb) | Maragheh et al. [[14]](#trident-references) | *HaloMNL* | [#](https://artefactory.github.io/choice-learn/references/models/halo_mnl/) |
+| Low-Rank Halo MNL | [notebook](notebooks/models/halo_mnl.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/halo_mnl.ipynb) | Ko and Li [[15]](#trident-references) | *LowRankHaloMNL* | [#](https://artefactory.github.io/choice-learn/references/models/halo_mnl/) |
 
-| NN-based Model    | Example | Colab | Related Paper | *from choice_learn.models import* | Doc |
+| NN-based Model | Example | Colab | Related Paper | *from choice_learn.models import* | Doc |
 | ---------- | -------- | ------ | ---- | ------ | :---: |
-| RUMnet| [notebook](notebooks/models/rumnet.ipynb) |  [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/rumnet.ipynb) |Aouad and Désir [[1]](#trident-references) | *RUMnet* | [#](https://artefactory.github.io/choice-learn/references/models/references_rumnet/#choice_learn.models.rumnet.PaperRUMnet) |
-| TasteNet | [notebook](notebooks/models/tastenet.ipynb) |  [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/tastenet.ipynb) |Han et al. [[7]](#trident-references) | *TasteNet* | [#](https://artefactory.github.io/choice-learn/references/models/references_tastenet/) |
-| Learning-MNL | [notebook](notebooks/models/learning_mnl.ipynb) |  [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/learning_mnl.ipynb) |Sifringer et al. [[13]](#trident-references) | *LearningMNL* | [#](https://artefactory.github.io/choice-learn/references/models/references_learning_mnl/) |
-| ResLogit | [notebook](notebooks/models/reslogit.ipynb) |  [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/reslogit.ipynb) |Wong and Farooq [[12]](#trident-references) | *ResLogit*  | [#](https://artefactory.github.io/choice-learn/references/models/references_reslogit/) |
+| RUMnet| [notebook](notebooks/models/rumnet.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/rumnet.ipynb) | Aouad and Désir [[1]](#trident-references) | *RUMnet* | [#](https://artefactory.github.io/choice-learn/references/models/references_rumnet/#choice_learn.models.rumnet.PaperRUMnet) |
+| TasteNet | [notebook](notebooks/models/tastenet.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/tastenet.ipynb) | Han et al. [[7]](#trident-references) | *TasteNet* | [#](https://artefactory.github.io/choice-learn/references/models/references_tastenet/) |
+| Learning-MNL | [notebook](notebooks/models/learning_mnl.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/learning_mnl.ipynb) | Sifringer et al. [[13]](#trident-references) | *LearningMNL* | [#](https://artefactory.github.io/choice-learn/references/models/references_learning_mnl/) |
+| ResLogit | [notebook](notebooks/models/reslogit.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/models/reslogit.ipynb) | Wong and Farooq [[12]](#trident-references) | *ResLogit* | [#](https://artefactory.github.io/choice-learn/references/models/references_reslogit/) |
+
+| Basket Model | Example | Colab | Related Paper | *from choice_learn.basket_models import* | Doc |
+| ---------- | -------- | ------ | ---- | ------ | :---: |
+| Deterministic SHOPPER| [notebook](notebooks/basket_models/shopper_tutorial.ipynb) | [![Open In Colab](https://img.shields.io/badge/-grey?logo=googlecolab)](https://colab.research.google.com/github/artefactory/choice-learn/blob/main/notebooks/basket_models/shopper_tutorial.ipynb) | Ruiz et al. [[16]](#trident-references) | *Shopper* | [#](https://artefactory.github.io/choice-learn/references/basket_models/references_shopper/) |
 
 
 ### Auxiliary tools
@@ -306,7 +310,8 @@ Choice-Learn has been developed through a collaboration between researchers at t
 [12] [ResLogit: A residual neural network logit model for data-driven choice modelling](https://doi.org/10.1016/j.trc.2021.103050), Wong, M.; Farooq, B. (2021)\
 [13] [Enhancing Discrete Choice Models with Representation Learning](https://arxiv.org/abs/1812.09747), Sifringer, B.; Lurkin, V.; Alahi, A. (2018)\
 [14] [A Customer Choice Model with HALO Effect](https://arxiv.org/abs/1805.01603), Maragheh, R., Y.; Chronopoulou, A.; Davis, J., M. (2018)\
-[15] [Modeling Choice via Self-Attention](https://arxiv.org/abs/2311.07607), Ko, J.; Li, A., A. (2023)
+[15] [Modeling Choice via Self-Attention](https://arxiv.org/abs/2311.07607), Ko, J.; Li, A., A. (2023)\
+[16] [SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements](https://arxiv.org/abs/1711.03560), Ruiz, F. J. R.; Athey, S.; Blei, D. M. (2019)
 
 ### Code and Repositories
 
@@ -315,4 +320,5 @@ Choice-Learn has been developed through a collaboration between researchers at t
 [1] [RUMnet](https://github.com/antoinedesir/rumnet)\
 [7] TasteNet [[Repo1](https://github.com/YafeiHan-MIT/TasteNet-MNL)] [[Repo2](https://github.com/deborahmit/TasteNet-MNL)]\
 [12] [ResLogit](https://github.com/LiTrans/reslogit)\
-[13] [Learning-MNL](https://github.com/BSifringer/EnhancedDCM)
+[13] [Learning-MNL](https://github.com/BSifringer/EnhancedDCM)\
+[16] [SHOPPER](https://github.com/franrruiz/shopper-src)

choice_learn/basket_models/__init__.py

@@ -0,0 +1,6 @@
+"""Models classes and functions."""
+
+from .shopper import Shopper
+from .trip_dataset import Trip, TripDataset
+
+__all__ = ["Shopper", "Trip", "TripDataset"]