Update README.md

[VincentAuriau]

add url for LPM dataset

[gemini-code-assist]

Code Review

This pull request updates the README.md file. The review feedback identifies a typo ('c') introduced at the start of the file and points out that the newly added URL for the London Passenger Mode Choice dataset was incorrectly placed in the Badminton Dataset row.

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[gemini-code-assist]

There is a typo 'c' introduced at the very beginning of the file before the 'div' tag.

Suggested change

	c<div align="center">
	<div align="center">

[gemini-code-assist]

The URL 'https://transp-or.epfl.ch/documents/technicalReports/CS_LPMC.pdf' is for the London Passenger Mode Choice (LPMC) dataset, but it has been added to the Badminton Dataset row instead. Please revert this change and place the URL in the London Passenger Mode Choice row (line 144) instead.

Suggested change

	| Badminton Dataset | [url](https://transp-or.epfl.ch/documents/technicalReports/CS_LPMC.pdf) | Désir et al. (2025) [[17]](#trident-references) | *BadmintonDataGenerator* | [#](https://artefactory.github.io/choice-learn/references/basket_models/datasets/badminton) |
	| Badminton Dataset | [url]() | Désir et al. (2025) [[17]](#trident-references) | *BadmintonDataGenerator* | [#](https://artefactory.github.io/choice-learn/references/basket_models/datasets/badminton) |

[github-actions]

Coverage Report for Python 3.10

File	Stmts	Miss	Cover	Missing
choice_learn
__init__.py	2	0	100%
tf_ops.py	64	1	98%	286
choice_learn/basket_models
__init__.py	4	0	100%
alea_carta.py	155	3	98%	111, 136, 326
base_basket_model.py	248	29	88%	115–116, 127, 145, 189, 259, 381, 489, 589–591, 680, 785, 793, 803, 851, 854–864, 925–928, 967–968
basic_attention_model.py	89	4	96%	424, 427, 433, 440
self_attention_model.py	133	9	93%	71, 73, 75, 450–454, 651
shopper.py	184	9	95%	130, 159, 325, 345, 360, 363, 377, 489, 618
choice_learn/basket_models/data
__init__.py	2	0	100%
basket_dataset.py	195	62	68%	74–77, 223–231, 299–301, 411, 544–580, 608–648, 671, 678–683, 753–764, 812
preprocessing.py	94	78	17%	43–45, 128–364
choice_learn/basket_models/datasets
__init__.py	3	0	100%
badminton.py	81	6	93%	62, 194–199, 247
bakery.py	38	3	92%	47, 51, 61
choice_learn/basket_models/utils
__init__.py	0	0	100%
permutation.py	22	1	95%	37
choice_learn/data
__init__.py	3	0	100%
choice_dataset.py	649	33	95%	198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1179–1181, 1209, 1214, 1223, 1240, 1281, 1293, 1307, 1346, 1361, 1366, 1395, 1408, 1443–1444
indexer.py	241	23	90%	20, 31, 45, 60–67, 202–204, 219–230, 265, 291, 582
storage.py	161	6	96%	22, 33, 51, 56, 61, 71
store.py	72	72	0%	3–275
choice_learn/datasets
__init__.py	4	0	100%
base.py	400	5	99%	42–43, 153–154, 714
expedia.py	102	83	19%	37–301
tafeng.py	49	0	100%
choice_learn/datasets/data
__init__.py	0	0	100%
choice_learn/models
__init__.py	14	2	86%	15–16
base_model.py	335	35	90%	145, 187, 289, 297, 303, 312, 352, 356–357, 362, 391, 395–396, 413, 426, 434, 475–476, 485–486, 587, 589, 605, 609, 611, 734–735, 935, 939–953
baseline_models.py	49	0	100%
conditional_logit.py	269	26	90%	49, 52, 54, 85, 88, 91–95, 98–102, 136, 206, 212–216, 351, 388, 445, 520–526, 651, 685, 822, 826
halo_mnl.py	124	2	98%	186, 374
latent_class_base_model.py	286	39	86%	55–61, 273–279, 288, 325–330, 497–500, 605, 624, 665–701, 715, 720, 751–752, 774–775, 869–870, 974
latent_class_mnl.py	62	6	90%	257–261, 296
learning_mnl.py	67	3	96%	157, 182, 188
nested_logit.py	291	12	96%	55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
reslogit.py	132	6	95%	285, 360, 369, 374, 382, 432
rumnet.py	236	3	99%	748–751, 982
simple_mnl.py	139	6	96%	167, 275, 347, 355, 357, 359
tastenet.py	94	3	97%	142, 180, 188
choice_learn/toolbox
__init__.py	0	0	100%
assortment_optimizer.py	27	6	78%	28–30, 93–95, 160–162
gurobi_opt.py	238	238	0%	3–675
or_tools_opt.py	230	11	95%	103, 107, 296–305, 315, 319, 607, 611
choice_learn/utils
metrics.py	116	7	94%	73, 151–153, 219–221, 287–289
TOTAL	5704	832	85%

Tests	Skipped	Failures	Errors	Time
228	0 💤	0 ❌	0 🔥	5m 27s ⏱️

[github-actions]

Coverage Report for Python 3.9

File	Stmts	Miss	Cover	Missing
choice_learn
__init__.py	2	0	100%
tf_ops.py	64	1	98%	286
choice_learn/basket_models
__init__.py	4	0	100%
alea_carta.py	155	3	98%	111, 136, 326
base_basket_model.py	248	29	88%	115–116, 127, 145, 189, 259, 381, 489, 589–591, 680, 785, 793, 803, 851, 854–864, 925–928, 967–968
basic_attention_model.py	89	4	96%	424, 427, 433, 440
self_attention_model.py	133	9	93%	71, 73, 75, 450–454, 651
shopper.py	184	9	95%	130, 159, 325, 345, 360, 363, 377, 489, 618
choice_learn/basket_models/data
__init__.py	2	0	100%
basket_dataset.py	195	62	68%	74–77, 223–231, 299–301, 411, 544–580, 608–648, 671, 678–683, 753–764, 812
preprocessing.py	94	78	17%	43–45, 128–364
choice_learn/basket_models/datasets
__init__.py	3	0	100%
badminton.py	81	6	93%	62, 194–199, 247
bakery.py	38	3	92%	47, 51, 61
choice_learn/basket_models/utils
__init__.py	0	0	100%
permutation.py	22	1	95%	37
choice_learn/data
__init__.py	3	0	100%
choice_dataset.py	649	33	95%	198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1179–1181, 1209, 1214, 1223, 1240, 1281, 1293, 1307, 1346, 1361, 1366, 1395, 1408, 1443–1444
indexer.py	241	23	90%	20, 31, 45, 60–67, 202–204, 219–230, 265, 291, 582
storage.py	161	6	96%	22, 33, 51, 56, 61, 71
store.py	72	72	0%	3–275
choice_learn/datasets
__init__.py	4	0	100%
base.py	400	5	99%	42–43, 153–154, 714
expedia.py	102	83	19%	37–301
tafeng.py	49	0	100%
choice_learn/datasets/data
__init__.py	0	0	100%
choice_learn/models
__init__.py	14	2	86%	15–16
base_model.py	335	34	90%	145, 187, 289, 297, 303, 312, 352, 356–357, 362, 391, 395–396, 413, 426, 434, 475–476, 485–486, 587, 589, 605, 609, 734–735, 935, 939–953
baseline_models.py	49	0	100%
conditional_logit.py	269	26	90%	49, 52, 54, 85, 88, 91–95, 98–102, 136, 206, 212–216, 351, 388, 445, 520–526, 651, 685, 822, 826
halo_mnl.py	124	18	85%	186, 341, 360, 364–380
latent_class_base_model.py	286	39	86%	55–61, 273–279, 288, 325–330, 497–500, 605, 624, 665–701, 715, 720, 751–752, 774–775, 869–870, 974
latent_class_mnl.py	62	6	90%	257–261, 296
learning_mnl.py	67	3	96%	157, 182, 188
nested_logit.py	291	12	96%	55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
reslogit.py	132	7	95%	122, 285, 360, 369, 374, 382, 432
rumnet.py	236	3	99%	748–751, 982
simple_mnl.py	139	6	96%	167, 275, 347, 355, 357, 359
tastenet.py	94	3	97%	142, 180, 188
choice_learn/toolbox
__init__.py	0	0	100%
assortment_optimizer.py	27	6	78%	28–30, 93–95, 160–162
gurobi_opt.py	236	236	0%	3–675
or_tools_opt.py	230	11	95%	103, 107, 296–305, 315, 319, 607, 611
choice_learn/utils
metrics.py	116	73	37%	71–105, 115, 149–173, 183, 217–240, 250, 285–309, 319
TOTAL	5702	912	84%

Tests	Skipped	Failures	Errors	Time
228	0 💤	1 ❌	0 🔥	7m 0s ⏱️

[github-actions]

Coverage Report for Python 3.11

File	Stmts	Miss	Cover	Missing
choice_learn
__init__.py	2	0	100%
tf_ops.py	64	1	98%	286
choice_learn/basket_models
__init__.py	4	0	100%
alea_carta.py	155	3	98%	111, 136, 326
base_basket_model.py	248	29	88%	115–116, 127, 145, 189, 259, 381, 489, 589–591, 680, 785, 793, 803, 851, 854–864, 925–928, 967–968
basic_attention_model.py	89	4	96%	424, 427, 433, 440
self_attention_model.py	133	9	93%	71, 73, 75, 450–454, 651
shopper.py	184	9	95%	130, 159, 325, 345, 360, 363, 377, 489, 618
choice_learn/basket_models/data
__init__.py	2	0	100%
basket_dataset.py	195	62	68%	74–77, 223–231, 299–301, 411, 544–580, 608–648, 671, 678–683, 753–764, 812
preprocessing.py	94	78	17%	43–45, 128–364
choice_learn/basket_models/datasets
__init__.py	3	0	100%
badminton.py	81	6	93%	62, 194–199, 247
bakery.py	38	3	92%	47, 51, 61
choice_learn/basket_models/utils
__init__.py	0	0	100%
permutation.py	22	1	95%	37
choice_learn/data
__init__.py	3	0	100%
choice_dataset.py	649	33	95%	198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1179–1181, 1209, 1214, 1223, 1240, 1281, 1293, 1307, 1346, 1361, 1366, 1395, 1408, 1443–1444
indexer.py	241	23	90%	20, 31, 45, 60–67, 202–204, 219–230, 265, 291, 582
storage.py	161	6	96%	22, 33, 51, 56, 61, 71
store.py	72	72	0%	3–275
choice_learn/datasets
__init__.py	4	0	100%
base.py	400	5	99%	42–43, 153–154, 714
expedia.py	102	83	19%	37–301
tafeng.py	49	0	100%
choice_learn/datasets/data
__init__.py	0	0	100%
choice_learn/models
__init__.py	14	2	86%	15–16
base_model.py	335	36	89%	145, 187, 289, 297, 303, 312, 352, 356–357, 362, 391, 395–396, 413, 426, 434, 475–476, 485–486, 587, 589, 605, 609, 611, 734–735, 908, 935, 939–953
baseline_models.py	49	0	100%
conditional_logit.py	269	26	90%	49, 52, 54, 85, 88, 91–95, 98–102, 136, 206, 212–216, 351, 388, 445, 520–526, 651, 685, 822, 826
halo_mnl.py	124	2	98%	186, 374
latent_class_base_model.py	286	39	86%	55–61, 273–279, 288, 325–330, 497–500, 605, 624, 665–701, 715, 720, 751–752, 774–775, 869–870, 974
latent_class_mnl.py	62	6	90%	257–261, 296
learning_mnl.py	67	3	96%	157, 182, 188
nested_logit.py	291	12	96%	55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
reslogit.py	132	6	95%	285, 360, 369, 374, 382, 432
rumnet.py	236	3	99%	748–751, 982
simple_mnl.py	139	6	96%	167, 275, 347, 355, 357, 359
tastenet.py	94	3	97%	142, 180, 188
choice_learn/toolbox
__init__.py	0	0	100%
assortment_optimizer.py	27	6	78%	28–30, 93–95, 160–162
gurobi_opt.py	238	238	0%	3–675
or_tools_opt.py	230	11	95%	103, 107, 296–305, 315, 319, 607, 611
choice_learn/utils
metrics.py	116	7	94%	73, 151–153, 219–221, 287–289
TOTAL	5704	833	85%

Tests	Skipped	Failures	Errors	Time
228	0 💤	0 ❌	0 🔥	7m 23s ⏱️

[github-actions]

Coverage Report for Python 3.12

File	Stmts	Miss	Cover	Missing
choice_learn
__init__.py	2	0	100%
tf_ops.py	64	1	98%	286
choice_learn/basket_models
__init__.py	4	0	100%
alea_carta.py	155	3	98%	111, 136, 326
base_basket_model.py	248	29	88%	115–116, 127, 145, 189, 259, 381, 489, 589–591, 680, 785, 793, 803, 851, 854–864, 925–928, 967–968
basic_attention_model.py	89	4	96%	424, 427, 433, 440
self_attention_model.py	133	9	93%	71, 73, 75, 450–454, 651
shopper.py	184	9	95%	130, 159, 325, 345, 360, 363, 377, 489, 618
choice_learn/basket_models/data
__init__.py	2	0	100%
basket_dataset.py	195	62	68%	74–77, 223–231, 299–301, 411, 544–580, 608–648, 671, 678–683, 753–764, 812
preprocessing.py	94	78	17%	43–45, 128–364
choice_learn/basket_models/datasets
__init__.py	3	0	100%
badminton.py	81	6	93%	62, 194–199, 247
bakery.py	38	3	92%	47, 53, 61
choice_learn/basket_models/utils
__init__.py	0	0	100%
permutation.py	22	1	95%	37
choice_learn/data
__init__.py	3	0	100%
choice_dataset.py	649	33	95%	198, 250, 283, 421, 463–464, 589, 724, 738, 840, 842, 937, 957–961, 1140, 1159–1161, 1179–1181, 1209, 1214, 1223, 1240, 1281, 1293, 1307, 1346, 1361, 1366, 1395, 1408, 1443–1444
indexer.py	241	23	90%	20, 31, 45, 60–67, 202–204, 219–230, 265, 291, 582
storage.py	161	6	96%	22, 33, 51, 56, 61, 71
store.py	72	72	0%	3–275
choice_learn/datasets
__init__.py	4	0	100%
base.py	400	5	99%	42–43, 153–154, 714
expedia.py	102	83	19%	37–301
tafeng.py	49	0	100%
choice_learn/datasets/data
__init__.py	0	0	100%
choice_learn/models
__init__.py	14	2	86%	15–16
base_model.py	335	35	90%	145, 187, 289, 297, 303, 312, 352, 356–357, 362, 391, 395–396, 413, 426, 434, 475–476, 485–486, 587, 589, 605, 609, 611, 734–735, 935, 939–953
baseline_models.py	49	0	100%
conditional_logit.py	269	26	90%	49, 52, 54, 85, 88, 91–95, 98–102, 136, 206, 212–216, 351, 388, 445, 520–526, 651, 685, 822, 826
halo_mnl.py	124	18	85%	186, 341, 360, 364–380
latent_class_base_model.py	286	39	86%	55–61, 273–279, 288, 325–330, 497–500, 605, 624, 665–701, 715, 720, 751–752, 774–775, 869–870, 974
latent_class_mnl.py	62	6	90%	257–261, 296
learning_mnl.py	67	3	96%	157, 182, 188
nested_logit.py	291	12	96%	55, 77, 160, 269, 351, 484, 530, 600, 679, 848, 900, 904
reslogit.py	132	6	95%	285, 360, 369, 374, 382, 432
rumnet.py	236	3	99%	748–751, 982
simple_mnl.py	139	6	96%	167, 275, 347, 355, 357, 359
tastenet.py	94	3	97%	142, 180, 188
choice_learn/toolbox
__init__.py	0	0	100%
assortment_optimizer.py	27	6	78%	28–30, 93–95, 160–162
gurobi_opt.py	238	238	0%	3–675
or_tools_opt.py	230	11	95%	103, 107, 296–305, 315, 319, 607, 611
choice_learn/utils
metrics.py	116	7	94%	73, 151–153, 219–221, 287–289
TOTAL	5704	848	85%

Tests	Skipped	Failures	Errors	Time
228	0 💤	1 ❌	0 🔥	6m 8s ⏱️