{ "data_id": "43828", "name": "Another-Dataset-on-used-Fiat-500-(1538-rows)", "exact_name": "Another-Dataset-on-used-Fiat-500-(1538-rows)", "version": 1, "version_label": "v1.0", "description": "This dataset has been created from a query done on an website specialized in used cars and contains 1538 rows\nDescription of colums:\nmodel: Fiat 500 comes in several 'flavours' :'pop', 'lounge', 'sport'\nengine_power: number of Kw of the engine\nageindays: age of the car in number of days (from the time the dataset has been created)\nkm: kilometers of the car\nprevious_owners: number of previous owners\nlat: latitude of the seller (the price of cars in Italy varies from North to South of the country)\nlon: longitude of the seller (the price of cars in Italy varies from North to South of the country)\nprice: selling price (the target)\nI collected this dataset to train myself and test regression algorithms. Hope this can help people to train as well.", "format": "arff", "uploader": "Elif Ceren Gok", "uploader_id": 30125, "visibility": "public", "creator": null, "contributor": null, "date": "2022-03-24 15:31:24", "update_comment": null, "last_update": "2022-03-24 15:31:24", "licence": "CC0: Public Domain", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/22102653\/dataset", "default_target_attribute": "price", "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "Another-Dataset-on-used-Fiat-500-(1538-rows)", "This dataset has been created from a query done on an website specialized in used cars and contains 1538 rows Description of colums: model: Fiat 500 comes in several 'flavours' :'pop', 'lounge', 'sport' engine_power: number of Kw of the engine ageindays: age of the car in number of days (from the time the dataset has been created) km: kilometers of the car previous_owners: number of previous owners lat: latitude of the seller (the price of cars in Italy varies from North to South of the country) " ], "weight": 5 }, "qualities": { "NumberOfInstances": 1538, "NumberOfFeatures": 8, "NumberOfClasses": 0, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 7, "NumberOfSymbolicFeatures": 0, "Dimensionality": 0.005201560468140442, "PercentageOfNumericFeatures": 87.5, "MajorityClassPercentage": null, "PercentageOfSymbolicFeatures": 0, "MajorityClassSize": null, "MinorityClassPercentage": null, "MinorityClassSize": null, "NumberOfBinaryFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 0, "AutoCorrelation": -2111.434612882238, "PercentageOfMissingValues": 0 }, "tags": [ { "uploader": "38960", "tag": "Agriculture" }, { "uploader": "38960", "tag": "Machine Learning" } ], "features": [ { "name": "price", "index": "7", "type": "numeric", "distinct": "222", "missing": "0", "target": "1", "min": "2500", "max": "11100", "mean": "8576", "stdev": "1940" }, { "name": "model", "index": "0", "type": "string", "distinct": "3", "missing": "0" }, { "name": "engine_power", "index": "1", "type": "numeric", "distinct": "8", "missing": "0", "min": "51", "max": "77", "mean": "52", "stdev": "4" }, { "name": "age_in_days", "index": "2", "type": "numeric", "distinct": "140", "missing": "0", "min": "366", "max": "4658", "mean": "1651", "stdev": "1290" }, { "name": "km", "index": "3", "type": "numeric", "distinct": "988", "missing": "0", "min": "1232", "max": "235000", "mean": "53396", "stdev": "40047" }, { "name": "previous_owners", "index": "4", "type": "numeric", "distinct": "4", "missing": "0", "min": "1", "max": "4", "mean": "1", "stdev": "0" }, { "name": "lat", "index": "5", "type": "numeric", "distinct": "449", "missing": "0", "min": "37", "max": "47", "mean": "44", "stdev": "2" }, { "name": "lon", "index": "6", "type": "numeric", "distinct": "450", "missing": "0", "min": "7", "max": "18", "mean": "12", "stdev": "2" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 0, "total_downloads": 0, "reach": 0, "reuse": 0, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 0 }