{ "data_id": "43485", "name": "Dollar-Stock-Prices-and-infos", "exact_name": "Dollar-Stock-Prices-and-infos", "version": 1, "version_label": "v1.0", "description": "Context\nTo build a AI to predict the stock price of the Dollar currency on IBOVESPA I had to make this dataset.\nAll information collected here is from a standard graphic for stock prices.\nContent\nThe data is organized by prices and infos per minute.\nEach row contains:\ndate, open price, maximim value, minimum value, close price, volume, financial, negotiations, mme13, mme72, high mean, low mean ,diffMACD, deaMACD, MACDlh, difflh, dealh, target.\nThe target columns is the price 15 minutes in the future.\nInspiration\nThis data is here to construct an Artificial Intelligence to predict the price in 15 minutes.\nWe want to buy if the predicted price is above of your goal per trade (mine goal is 8 point per trade) and sell if the prediction is below of your goal.", "format": "arff", "uploader": "Onur Yildirim", "uploader_id": 30126, "visibility": "public", "creator": null, "contributor": null, "date": "2022-03-23 13:27:03", "update_comment": null, "last_update": "2022-03-23 13:27:03", "licence": "CC0: Public Domain", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/22102310\/dataset", "default_target_attribute": null, "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "Dollar-Stock-Prices-and-infos", "Context To build a AI to predict the stock price of the Dollar currency on IBOVESPA I had to make this dataset. All information collected here is from a standard graphic for stock prices. Content The data is organized by prices and infos per minute. Each row contains: date, open price, maximim value, minimum value, close price, volume, financial, negotiations, mme13, mme72, high mean, low mean ,diffMACD, deaMACD, MACDlh, difflh, dealh, target. The target columns is the price 15 minutes in the fu " ], "weight": 5 }, "qualities": { "NumberOfInstances": 33077, "NumberOfFeatures": 18, "NumberOfClasses": null, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 17, "NumberOfSymbolicFeatures": 0, "Dimensionality": 0.0005441847809656257, "PercentageOfNumericFeatures": 94.44444444444444, "MajorityClassPercentage": null, "PercentageOfSymbolicFeatures": 0, "MajorityClassSize": null, "MinorityClassPercentage": null, "MinorityClassSize": null, "NumberOfBinaryFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 0, "AutoCorrelation": null, "PercentageOfMissingValues": 0 }, "tags": [ { "uploader": "38960", "tag": "Computer Systems" }, { "uploader": "38960", "tag": "Machine Learning" } ], "features": [ { "name": "21-11-19_09:03", "index": "0", "type": "string", "distinct": "33070", "missing": "0" }, { "name": "4206.0", "index": "1", "type": "numeric", "distinct": "2220", "missing": "0", "min": "4047", "max": "5246", "mean": "4461", "stdev": "336" }, { "name": "4206.5", "index": "2", "type": "numeric", "distinct": "2124", "missing": "0", "min": "4046", "max": "5260", "mean": "4462", "stdev": "337" }, { "name": "4204.5", "index": "3", "type": "numeric", "distinct": "2123", "missing": "0", "min": "4046", "max": "5242", "mean": "4459", "stdev": "336" }, { "name": "4206.0.1", "index": "4", "type": "numeric", "distinct": "2247", "missing": "0", "min": "4046", "max": "5249", "mean": "4461", "stdev": "336" }, { "name": "5024", "index": "5", "type": "numeric", "distinct": "8016", "missing": "0", "min": "11", "max": "74413", "mean": "2859", "stdev": "2710" }, { "name": "211292030.0", "index": "6", "type": "numeric", "distinct": "33051", "missing": "0", "min": "241516", "max": "2147483647", "mean": "129433083", "stdev": "123704253" }, { "name": "1443", "index": "7", "type": "numeric", "distinct": "3755", "missing": "0", "min": "11", "max": "17235", "mean": "899", "stdev": "921" }, { "name": "4201.6", "index": "8", "type": "numeric", "distinct": "8123", "missing": "0", "min": "4048", "max": "5237", "mean": "4460", "stdev": "336" }, { "name": "4202.4", "index": "9", "type": "numeric", "distinct": "8241", "missing": "0", "min": "4051", "max": "5221", "mean": "4459", "stdev": "335" }, { "name": "4202.8", "index": "10", "type": "numeric", "distinct": "8104", "missing": "0", "min": "4044", "max": "5241", "mean": "4462", "stdev": "337" }, { "name": "4201.2", "index": "11", "type": "numeric", "distinct": "8143", "missing": "0", "min": "4047", "max": "5233", "mean": "4459", "stdev": "335" }, { "name": "-0.637", "index": "12", "type": "numeric", "distinct": "11760", "missing": "0", "min": "-44", "max": "10", "mean": "0", "stdev": "4" }, { "name": "-0.126", "index": "13", "type": "numeric", "distinct": "10525", "missing": "0", "min": "-32", "max": "30", "mean": "0", "stdev": "4" }, { "name": "-0.125", "index": "14", "type": "numeric", "distinct": "6023", "missing": "0", "min": "-19", "max": "12", "mean": "0", "stdev": "1" }, { "name": "-0.44", "index": "15", "type": "numeric", "distinct": "8466", "missing": "0", "min": "-15", "max": "10", "mean": "0", "stdev": "2" }, { "name": "-0.377", "index": "16", "type": "numeric", "distinct": "8238", "missing": "0", "min": "-13", "max": "10", "mean": "0", "stdev": "2" }, { "name": "4200.0", "index": "17", "type": "numeric", "distinct": "2220", "missing": "0", "min": "4047", "max": "5246", "mean": "4461", "stdev": "337" } ], "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 }