Lymphography data set

1: Description.

This is a domain provided by the Oncology Institute that has repeatedly appeared in the machine learning literature. The task is to detect the presence of a lymphoma and its current status.

2: Type.			Classification	
3: Origin.			Real world
4: Instances.		148
5: Features.		18
6: Classes.			4	
7: Missing values.	No

8: Header.

@relation lymphography
@attribute Lymphatics {normal,arched,deformed,displaced}
@attribute Block_of_affere {no,yes}
@attribute Bl_of_lymph_c {no,yes}
@attribute Bl_of_lymph_s {no,yes}
@attribute By_pass {no,yes}
@attribute Extravasates {no,yes}
@attribute Regeneration_of {no,yes}
@attribute Early_uptake_in {no,yes}
@attribute Lym_nodes_dimin integer [0,3]
@attribute Lym_nodes_enlar integer [1,4]
@attribute Changes_in_lym {bean,oval,round}
@attribute Defect_in_node {no,lacunar,lac_margin,lac_central}
@attribute Changes_in_node {no,lacunar,lac_margin,lac_central}
@attribute Changes_in_stru {no,grainy,drop_like,coarse,diluted,reticular,stripped,faint}
@attribute Special_forms {no,chalices,vesicles}
@attribute Dislocation_of {no,yes}
@attribute Exclusion_of_no {no,yes}
@attribute No_of_nodes_in integer [1,8]
@attribute Class {normal,metastases,malign_lymph,fibrosis}
@inputs Lymphatics, Block_of_affere, Bl_of_lymph_c, Bl_of_lymph_s, By_pass, Extravasates, Regeneration_of, Early_uptake_in, Lym_nodes_dimin, Lym_nodes_enlar, Changes_in_lym, Defect_in_node, Changes_in_node, Changes_in_stru, Special_forms, Dislocation_of, Exclusion_of_no, No_of_nodes_in
@output Class