Datasets › Vehicle Claims

Vehicle Claims

Introduced by Ajay Chawda et al. in Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings25 Oct 2022 archive 2025-07-28

The code to create the dataset is available here. The dataset used in the paper is available on github

  • Maker - Categorical - The brand of the vehicle.
  • GenModel - Categorical - The model of the vehicle.
  • Color - Categorical - Colour of the vehicle.
  • Reg_Year - Categorical - Year of Registration.
  • Body_Type - Categorical - Eg. SUV, Convertible.
  • Runned_Miles - Numerical - Distance covered by the vehicle.
  • Engin_Size - Categorical - Size of engine.
  • GearBox - Categorical - Automatic, Manual.
  • FuelType - Categorical - Petrol, Diesel.
  • Price - Numerical - Price of vehicle.
  • Seat_num - Numerical - Number of seats.
  • Door_num - Numerical - Number of Doors.
  • issue - Categorical - Type of damage.
  • issue_id - Categorical - Specific damage.
  • repair_complexity - Categorical - Difficulty to repair the vehicle.
  • repair_hours - Numerical - Time required to finish the job.
  • repair_cost - Numerical - Cost of repair.

Other attributes are not used for evaluation in this work. breakdown_date and repair_date were added with the idea of inserting anomalies based on the number of days required to repair the vehicle.

Benchmarks archive 2025-07-28

All 2 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Unsupervised Anomaly Detection Vehicle Claims SOM AUC 65.43 Unsupervised Anomaly Detection for Auditing Data and... ajaychawda58/uadad 9 Compare
Anomaly Detection Vehicle Claims Random Forest AUC 98.65 Unsupervised Anomaly Detection for Auditing Data and... ajaychawda58/uadad 2 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 2. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings 1 11 25 Oct 2022 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • Vehicle Claims

1 variant name, as the archive lists them.

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