%% Source: %% %% The dataset was created by Angeliki Xifara (angxifara @ gmail.com, %% Civil/Structural Engineer) and was processed by Athanasios Tsanas %% (tsanasthanasis @ gmail.com, Oxford Centre for Industrial and Applied %% Mathematics, University of Oxford, UK). %% %% Data Set Information: %% %% We perform energy analysis using 12 different building shapes simulated in Ecotect. %% The buildings differ with respect to the glazing area, the glazing area distribution, %% and the orientation, amongst other parameters. We simulate various settings as functions %% of the afore-mentioned characteristics to obtain 768 building shapes. The dataset %% comprises 768 samples and 8 features, aiming to predict two real valued responses. It can %% also be used as a multi-class classification problem if the response is rounded to the %% nearest integer. %% %% Attribute Information: %% %% The dataset contains eight attributes (or features, denoted by X1...X8) and two responses %% (or outcomes, denoted by y1 and y2). The aim is to use the eight features to predict each of %% the two responses. %% %% Specifically: %% X1 Relative Compactness %% X2 Surface Area %% X3 Wall Area %% X4 Roof Area %% X5 Overall Height %% X6 Orientation %% X7 Glazing Area %% X8 Glazing Area Distribution %% y1 Heating Load %% y2 Cooling Load @relation energy-efficiency @attribute V1 numeric @attribute V2 numeric @attribute V3 numeric @attribute V4 numeric @attribute V5 numeric @attribute V6 numeric @attribute V7 numeric @attribute V8 numeric @attribute y1 {1,10,11,12,13,14,15,16,17,18,19,2,20,21,22,23,24,25,26,27,28,29,3,30,31,32,33,34,35,36,37,4,5,6,7,8,9} @attribute y2 {1,10,11,12,13,14,15,16,17,18,19,2,20,21,22,23,24,25,26,27,28,29,3,30,31,32,33,34,35,36,37,38,4,5,6,7,8,9} @data 0.98,514.5,294,110.25,7,2,0,0,7,11 0.98,514.5,294,110.25,7,3,0,0,7,11 0.98,514.5,294,110.25,7,4,0,0,7,11 0.98,514.5,294,110.25,7,5,0,0,7,11 0.9,563.5,318.5,122.5,7,2,0,0,12,18 0.9,563.5,318.5,122.5,7,3,0,0,12,15 0.9,563.5,318.5,122.5,7,4,0,0,12,15 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0.71,710.5,269.5,220.5,3.5,4,0.4,5,4,5 0.71,710.5,269.5,220.5,3.5,5,0.4,5,3,5 0.69,735,294,220.5,3.5,2,0.4,5,5,7 0.69,735,294,220.5,3.5,3,0.4,5,5,6 0.69,735,294,220.5,3.5,4,0.4,5,5,7 0.69,735,294,220.5,3.5,5,0.4,5,5,7 0.66,759.5,318.5,220.5,3.5,2,0.4,5,6,8 0.66,759.5,318.5,220.5,3.5,3,0.4,5,6,8 0.66,759.5,318.5,220.5,3.5,4,0.4,5,6,8 0.66,759.5,318.5,220.5,3.5,5,0.4,5,6,8 0.64,784,343,220.5,3.5,2,0.4,5,9,11 0.64,784,343,220.5,3.5,3,0.4,5,9,10 0.64,784,343,220.5,3.5,4,0.4,5,9,11 0.64,784,343,220.5,3.5,5,0.4,5,9,11 0.62,808.5,367.5,220.5,3.5,2,0.4,5,8,7 0.62,808.5,367.5,220.5,3.5,3,0.4,5,7,7 0.62,808.5,367.5,220.5,3.5,4,0.4,5,7,7 0.62,808.5,367.5,220.5,3.5,5,0.4,5,8,6