{"url":"/dataset/travel","name":"Travel","full_name":"Tour & Travels Customer Churn Prediction","description_markdown":"A Tour & Travels Company Wants To Predict Whether A Customer Will Churn Or Not Based On Indicators Given Below.\r\nHelp Build Predictive Models And Save The Company's Money.\r\nPerform Fascinating EDAs.\r\nThe Data Was Used For Practice Purposes And Also During A Mini Hackathon, Its Completely Free To Use","description_withheld":null,"homepage":"https://www.kaggle.com/datasets/tejashvi14/tour-travels-customer-churn-prediction","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"CCO","url":null},"modalities":[{"name":"Tabular","url":"/datasets/modality/tabular"}],"tasks":[{"name":"Tabular Data Generation","url":"/task/tabular-data-generation","datasets_with_task":"/datasets/task/tabular-data-generation"}],"languages":[{"name":"French","url":"/datasets/language/french"}],"variants":["Travel"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/tabular-data-generation-on-travel","task":"Tabular Data Generation","dataset_variant":"Travel","rows":6,"metrics":["DT Accuracy","LR Accuracy","RF Accuracy","Parameters(M)"],"first_row_in_archive_order":{"model":"Binary Diffusion","paper":"/paper/tabular-data-generation-using-binary","metrics":{"DT Accuracy":"88.9","LR Accuracy":"83.79","Parameters(M)":"1.1","RF Accuracy":"89.95"},"code_links":[{"title":"vkinakh/binary-diffusion-tabular","url":"https://github.com/vkinakh/binary-diffusion-tabular"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/tabular-data-generation-using-binary","title":"Tabular Data Generation using Binary Diffusion","date":"2024-09-20","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":10,"samples_ran":10,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/language-models-are-realistic-tabular-data","title":"Language Models are Realistic Tabular Data Generators","date":"2022-10-12","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":6,"samples_ran":6,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/modeling-tabular-data-using-conditional-gan","title":"Modeling Tabular data using Conditional GAN","date":"2019-07-01","rows_on_this_dataset":3,"code_links":9,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":3,"samples_harvested":19,"samples_ran":18,"samples_unverified":1,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}