From f16897dfe2629885e392b38505198755c58b1946 Mon Sep 17 00:00:00 2001 From: VincentAURIAU Date: Thu, 7 Mar 2024 14:35:56 +0100 Subject: [PATCH] ADD: details in ReadMe --- README.md | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 0ac60c06..40da1e8a 100644 --- a/README.md +++ b/README.md @@ -41,28 +41,28 @@ If you are new to choice modelling, you can check this [resource](https://www.pu ## What's in there ? ### Data -- Generic dataset handling with the ChoiceDataset class +- Generic dataset handling with the ChoiceDataset class [[Example]](https://github.com/artefactory/choice-learn-private/blob/main/notebooks/choice_learn_introduction_data.ipynb) - Ready-To-Use datasets: - [SwissMetro](./choice_learn/datasets/data/swissmetro.csv.gz) from Bierlaire et al. (2001) [[2]](#citation) - [ModeCanada](./choice_learn/datasets/data/ModeCanada.csv.gz) from Koppelman et al. (1993) [[3]](#citation) - - The [Train](./choice_learn/datasets/data/train_data.csv.gz) dataset from Ben Akiva et al. (1993) [5](#citation) + - The [Train](./choice_learn/datasets/data/train_data.csv.gz) dataset from Ben Akiva et al. (1993) [[5]](#citation) - The [Heating](./choice_learn/datasets/data/heating_data.csv.gz) & [Electricity](./choice_learn/datasets/data/electricity.csv.gz) datasets from Kenneth Train described [here](https://rdrr.io/cran/mlogit/man/Electricity.html) and [here](https://rdrr.io/cran/mlogit/man/Heating.html) - The [TaFeng](./choice_learn/datasets/data/ta_feng.csv.zip) dataset from [Kaggle](https://www.kaggle.com/datasets/chiranjivdas09/ta-feng-grocery-dataset) ### Models - Ready-to-use models: - - Conditional MultiNomialLogit, Train, K.; McFadden, D.; Ben-Akiva, M. (1987) [[4]](#citation) - - RUMnet, Aouad A.; Désir A. (2022) [[1]](#citation) + - Conditional MultiNomialLogit, Train, K.; McFadden, D.; Ben-Akiva, M. (1987) [[4]](#citation)[[Example]](https://github.com/artefactory/choice-learn-private/blob/main/notebooks/choice_learn_introduction_clogit.ipynb) + - Latent Class MultiNomialLogit [[Example]](https://github.com/artefactory/choice-learn-private/blob/main/notebooks/latent_class_model.ipynb) + - RUMnet, Aouad A.; Désir A. (2022) [[1]](#citation)[[Example]](https://github.com/artefactory/choice-learn-private/blob/main/notebooks/rumnet_example.ipynb) - Ready-to-use models to be implemented: - Nested MultiNomialLogit - - MultiNomialLogit with latent variables (MixedLogit) - [TasteNet](https://arxiv.org/abs/2002.00922) - [SHOPPER](https://projecteuclid.org/journals/annals-of-applied-statistics/volume-14/issue-1/SHOPPER--A-probabilistic-model-of-consumer-choice-with-substitutes/10.1214/19-AOAS1265.full) - Others ... -- Custom modelling is made easy by subclassing the ChoiceModel class +- Custom modelling is made easy by subclassing the ChoiceModel class [[Example]](https://github.com/artefactory/choice-learn-private/blob/main/notebooks/custom_model.ipynb) ### Different tools -- Assortment optimization from model +- Assortment optimization from model [[Example]](https://github.com/artefactory/choice-learn-private/blob/main/notebooks/assortment_example.ipynb) - (WIP) Standardization of evaluation protocols - (WIP) Interfaces @@ -148,6 +148,7 @@ A detailed documentation of this project is available [here](https://artefactory ## Citation ### Contributors +### Special Thanks ## References