CoolFace
Datasetpublic

samgohan/Tabular_Imbalanced_Regression

Tabular Imbalanced Regression Datasets Repository Summary This repository provides a collection of 81 tabular datasets curated for research on tabular imbalanced regression problems. They were obtained from the various studies carried out on the subject (source and papers listed below).Its objective is to centralize datasets commonly used in the literature, serving as a solid reference point for future work. Additional datasets can be contributed or requested —… See the full description on the dataset page: https://huggingface.co/datasets/samgohan/Tabular_Imbalanced_Regression.

sourceHugging Facecc-by-4.0updated 1y agoView on Hugging Face
1likes149downloads
cocomo_numeric.csv62 linesDownload Raw Back to TIR_datasets
1target,onehotencoder__x0_High,onehotencoder__x0_Low,onehotencoder__x0_Nominal,onehotencoder__x0_Very_High,onehotencoder__x1_High,onehotencoder__x1_Low,onehotencoder__x1_Nominal,onehotencoder__x1_Very_High,onehotencoder__x2_Extra_High,onehotencoder__x2_High,onehotencoder__x2_Low,onehotencoder__x2_Nominal,onehotencoder__x2_Very_High,onehotencoder__x3_Extra_High,onehotencoder__x3_High,onehotencoder__x3_Nominal,onehotencoder__x3_Very_High,onehotencoder__x4_Extra_High,onehotencoder__x4_High,onehotencoder__x4_Nominal,onehotencoder__x4_Very_High,onehotencoder__x5_High,onehotencoder__x5_Low,onehotencoder__x5_Nominal,onehotencoder__x6_High,onehotencoder__x6_Low,onehotencoder__x6_Nominal,onehotencoder__x7_High,onehotencoder__x7_Nominal,onehotencoder__x7_Very_High,onehotencoder__x8_High,onehotencoder__x8_Nominal,onehotencoder__x8_Very_High,onehotencoder__x9_High,onehotencoder__x9_Nominal,onehotencoder__x9_Very_High,onehotencoder__x10_High,onehotencoder__x10_Low,onehotencoder__x10_Nominal,onehotencoder__x11_High,onehotencoder__x11_Low,onehotencoder__x11_Nominal,onehotencoder__x11_Very_Low,onehotencoder__x12_High,onehotencoder__x12_Low,onehotencoder__x12_Nominal,onehotencoder__x12_Very_High,onehotencoder__x13_High,onehotencoder__x13_Low,onehotencoder__x13_Nominal,onehotencoder__x13_Very_High,onehotencoder__x13_Very_Low,onehotencoder__x14_High,onehotencoder__x14_Low,onehotencoder__x14_Nominal,LOC2278.0,0,0,1.0,0,1.0,0,0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,70.031181.0,0,0,0,1.0,1.0,0,0,0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,227.041248.0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,1.0,0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,177.95480.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,115.86120.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,29.5760.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,19.78300.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,66.6918.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,5.51050.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,10.41160.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,14.012114.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,16.01342.0,1.0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,6.51460.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,13.01542.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,8.016450.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,0,1.0,90.01790.0,1.0,0,0,0,0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,15.018210.0,1.0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,38.01948.0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,10.020815.0,0,0,1.0,0,0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,161.121239.0,0,0,1.0,0,0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,48.522170.0,0,0,1.0,0,0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,32.62362.0,0,0,1.0,0,0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,12.82470.0,0,0,1.0,0,0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,15.42582.0,0,0,1.0,0,0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,16.326192.0,0,0,1.0,0,0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,35.527117.6,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,25.928117.6,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,24.62931.2,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,7.73025.2,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,9.7318.4,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,2.23210.8,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,3.53336.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,8.234352.8,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,66.635324.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,0,1.0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,150.036360.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,100.037215.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,100.038360.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,0,1.0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,100.03948.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,15.04060.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,32.54160.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,31.54224.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,6.04336.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,11.34472.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,0,1.0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,20.04548.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,20.04672.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,0,1.0,7.5472400.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,0,0,1.0,0,0,1.0,302.0483240.0,1.0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,370.0492120.0,1.0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,219.050370.0,1.0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,50.051750.0,1.0,0,0,0,0,0,1.0,0,0,0,0,0,1.0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,0,0,0,1.0,0,1.0,0,0,101.052420.0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,0,1.0,0,0,1.0,0,1.0,0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,0,1.0,190.053252.0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,1.0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,1.0,0,0,47.554107.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,0,0,0,1.0,21.0552300.0,0,1.0,0,0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,0,0,0,1.0,0,0,1.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,423.056400.0,1.0,0,0,0,1.0,0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,1.0,0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,0,1.0,79.057973.0,1.0,0,0,0,1.0,0,0,0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,1.0,0,0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,0,0,1.0,0,0,0,0,1.0,284.7581368.0,0,0,1.0,0,1.0,0,0,0,0,0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,1.0,0,0,0,0,1.0,1.0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,1.0,0,1.0,0,0,0,1.0,0,0,0,0,0,0,1.0,282.159571.4,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,78.06098.8,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,11.461155.0,0,0,1.0,0,1.0,0,0,0,0,1.0,0,0,0,0,0,0,1.0,0,0,1.0,0,0,0,1.0,1.0,0,0,1.0,0,0,1.0,0,0,1.0,0,0,0,0,1.0,1.0,0,0,0,0,1.0,0,0,0,1.0,0,0,0,1.0,0,0,19.362