{ "data_id": "43873", "name": "sarcos", "exact_name": "sarcos", "version": 3, "version_label": null, "description": "**Dataset Description**\n\nThe data relates to an inverse dynamics problem for a seven degrees-of-freedom\nSARCOS anthropomorphic robot arm. The task is to map from a 21-dimensional\ninput space (7 joint positions, 7 joint velocities, 7 joint accelerations) to\nthe corresponding 7 joint torques. Usually, the first of those (V22) is used as\nthe target variable and is therefore set as the default target variable, while\nthe other 6 joint torques are excluded from the model.\n\n\n**NOTE**\n\nThis dataset contains only the corresponding training data, as there is data leakage between\nthe original training and test data. This was described in\n[this article](https:\/\/www.datarobot.com\/blog\/running-code-and-failing-models\/) by Rajiv Shah.\n\n\n**Related Studies**\n\n * LWPR: An O(n) Algorithm for Incremental Real Time Learning in High\n Dimensional Space, S. Vijayakumar and S. Schaal, Proc ICML 2000, 1079-1086\n\n * (2000). Statistical Learning for Humanoid Robots, S. Vijayakumar, A.\n D'Souza, T. Shibata, J. Conradt, S. Schaal, Autonomous Robot, 12(1) 55-69\n\n * (2002) Incremental Online Learning in High Dimensions S. Vijayakumar, A.\n D'Souza, S. Schaal, Neural Computation 17(12) 2602-2634 (2005)\n\n * (2019) Cascaded Gaussian Processes for Data-efficient Robot Dynamics Learning,\n Sahand Rezaei-Shoshtari, David Meger, Inna Sharf, https:\/\/arxiv.org\/pdf\/1910.02291.pdf\n\n * (2019) TabNet: Attentive Interpretable Tabular Learning,\n Sercan Oe. Arik, Tomas Pfister, https:\/\/arxiv.org\/pdf\/1908.07442.pdf\n\n**Citation**\n\nLWPR: An O(n) Algorithm for Incremental Real-Time Learning in High Dimensional Space, S. Vijayakumar and S. Schaal, Proc ICML 2000, 1079-1086 (2000).\n\nThe data was obtained from: http:\/\/www.gaussianprocess.org\/gpml\/data\/", "format": "arff", "uploader": "Sebastian Fischer", "uploader_id": 30127, "visibility": "public", "creator": null, "contributor": null, "date": "2022-04-20 17:44:43", "update_comment": null, "last_update": "2022-04-20 17:44:43", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/old.openml.org\/data\/download\/22102750\/data.arff", "default_target_attribute": "V22", "row_id_attribute": null, "ignore_attribute": "\"V23\",\"V24\",\"V25\",\"V26\",\"V27\",\"V28\"", "runs": 0, "suggest": { "input": [ "sarcos", "The data relates to an inverse dynamics problem for a seven degrees-of-freedom SARCOS anthropomorphic robot arm. The task is to map from a 21-dimensional input space (7 joint positions, 7 joint velocities, 7 joint accelerations) to the corresponding 7 joint torques. Usually, the first of those (V22) is used as the target variable and is therefore set as the default target variable, while the other 6 joint torques are excluded from the model. This dataset contains only the corresponding training " ], "weight": 5 }, "qualities": { "NumberOfInstances": 44484, "NumberOfFeatures": 22, "NumberOfClasses": 0, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 22, "NumberOfSymbolicFeatures": 0, "MajorityClassPercentage": null, "PercentageOfSymbolicFeatures": 0, "MajorityClassSize": null, "MinorityClassPercentage": null, "MinorityClassSize": null, "NumberOfBinaryFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 0, "AutoCorrelation": -1.856855835712428, "PercentageOfMissingValues": 0, "Dimensionality": 0.0004945598417408506, "PercentageOfNumericFeatures": 100 }, "tags": [ { "uploader": "38960", "tag": "Machine Learning" }, { "uploader": "38960", "tag": "Statistics" } ], "features": [ { "name": "V22", "index": "21", "type": "numeric", "distinct": "11411", "missing": "0", "target": "1", "min": "-95", "max": "121", "mean": "14", "stdev": "20" }, { 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