multi-output regression datasets

you can download these datasets from OpenML: https://www.openml.org/search?type=data&status=active&tags.tag=2019_multioutput_paper. EDM: The Electrical Discharge Machining dataset (Karalic and Bratko 1997) represents a two-target regression problem. The task is to shorten the machining time by reproducing the behaviour of a human operator that controls the values of two variables. Each of the target variables takes 3 distinct numeric values ( -1,0,1 ) and there are 16 continuous input variables.WQ: The Water Quality dataset (Dzeroski et al. 2000) has 14 target attributes that refer to the relative representation of plant and animal species in Slovenian rivers and 16 input attributes that refer to physical and chemical water quality parameters.ENB: The Energy Building dataset (Tsanas and Xifara 2012) concerns the prediction of the heating load and cooling load requirements of buildings (i.e. energy efficiency) as a function of eight building parameters such as glazing area, roof area, and overall height, amongst others.

您可从OpenML下载以下数据集：https://www.openml.org/search?type=data&status=active&tags.tag=2019_multioutput_paper。
EDM：电火花加工（Electrical Discharge Machining）数据集（Karalic与Bratko，1997）属于双目标回归任务。其研究目标为复现人类操作员对两个变量的调控行为，以缩短加工时长。该数据集的两个目标变量均包含3个离散数值（-1、0、1），同时包含16个连续型输入变量。
WQ：水质（Water Quality）数据集（Dzeroski等，2000）包含14个目标属性，用于表征斯洛文尼亚河流中动植物物种的相对占比；另有16个输入属性，对应水体的物理与化学水质参数。
ENB：建筑能耗（Energy Building）数据集（Tsanas与Xifara，2012）旨在基于八项建筑参数（如玻璃面积、屋顶面积、总高度等），预测建筑的采暖负荷与制冷负荷需求，即能源效率。