{"id":"https://openalex.org/W7154234727","doi":"https://doi.org/10.48550/arxiv.2604.11200","title":"ShapShift: Explaining Model Prediction Shifts with Subgroup Conditional Shapley Values","display_name":"ShapShift: Explaining Model Prediction Shifts with Subgroup Conditional Shapley Values","publication_year":2026,"publication_date":"2026-04-13","ids":{"openalex":"https://openalex.org/W7154234727","doi":"https://doi.org/10.48550/arxiv.2604.11200"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.11200","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11200","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.11200","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017714952","display_name":"Tom Bewley","orcid":"https://orcid.org/0000-0002-5460-0744"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bewley, Tom","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059415532","display_name":"Salim I. Amoukou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amoukou, Salim I.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007110035","display_name":"Emanuele Albini","orcid":"https://orcid.org/0000-0003-2964-4638"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Albini, Emanuele","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133591064","display_name":"Saumitra Mishra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mishra, Saumitra","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126936837","display_name":"Manuela Veloso","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Veloso, Manuela","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9678999781608582,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9678999781608582,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.005400000140070915,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.004100000020116568,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/shapley-value","display_name":"Shapley value","score":0.5697000026702881},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5116000175476074},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.48159998655319214},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.44609999656677246},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4390999972820282},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.37139999866485596},{"id":"https://openalex.org/keywords/conditional-probability","display_name":"Conditional probability","score":0.35499998927116394},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.34279999136924744}],"concepts":[{"id":"https://openalex.org/C199022921","wikidata":"https://www.wikidata.org/wiki/Q240046","display_name":"Shapley value","level":3,"score":0.5697000026702881},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5116000175476074},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5095000267028809},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45980000495910645},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.44609999656677246},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4390999972820282},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4147999882698059},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.37139999866485596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3621000051498413},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3379000127315521},{"id":"https://openalex.org/C186215838","wikidata":"https://www.wikidata.org/wiki/Q772232","display_name":"Conditional expectation","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C84839998","wikidata":"https://www.wikidata.org/wiki/Q5249245","display_name":"Decision rule","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.26510000228881836},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26440000534057617},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2587999999523163},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.11200","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11200","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.11200","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.11200","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6269397735595703}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Changes":[0],"in":[1,7,49,159],"input":[2],"distribution":[3],"can":[4,33,132],"induce":[5],"shifts":[6,17,46,152],"the":[8,50,64,98],"average":[9],"predictions":[10],"of":[11,53,56,66,150],"machine":[12],"learning":[13],"models.":[14],"Such":[15],"prediction":[16,45,151],"may":[18],"impact":[19],"downstream":[20],"business":[21],"outcomes":[22],"(e.g.":[23],"a":[24,39,110,118],"bank's":[25],"loan":[26],"approval":[27],"rate),":[28],"so":[29],"understanding":[30],"their":[31],"causes":[32],"be":[34,133],"crucial.":[35],"We":[36,69,140],"propose":[37,109],"\\ours{}:":[38],"Shapley":[40],"value":[41],"method":[42,73],"for":[43,104],"attributing":[44],"to":[47,74,93,124],"changes":[48,85],"conditional":[51,83],"probabilities":[52],"interpretable":[54],"subgroups":[55,60],"data,":[57],"where":[58],"these":[59],"are":[61],"defined":[62],"by":[63,96],"structure":[65],"decision":[67,76],"trees.":[68],"initially":[70],"apply":[71],"this":[72],"single":[75],"trees,":[77],"providing":[78],"exact":[79,130],"explanations":[80,149],"based":[81],"on":[82],"probability":[84],"at":[86],"split":[87],"nodes.":[88],"Next,":[89],"we":[90,108],"extend":[91],"it":[92],"tree":[94,101],"ensembles":[95],"selecting":[97],"most":[99],"explanatory":[100],"and":[102,147],"accounting":[103],"residual":[105],"effects.":[106],"Finally,":[107],"model-agnostic":[111],"variant":[112],"using":[113],"surrogate":[114],"trees":[115],"grown":[116],"with":[117],"novel":[119],"objective":[120],"function,":[121],"allowing":[122],"application":[123],"models":[125],"like":[126],"neural":[127],"networks.":[128],"While":[129],"computation":[131],"intensive,":[134],"approximation":[135],"techniques":[136],"enable":[137],"practical":[138],"application.":[139],"show":[141],"that":[142],"\\ours{}":[143],"provides":[144],"simple,":[145],"faithful,":[146],"near-complete":[148],"across":[153],"model":[154,157],"classes,":[155],"aiding":[156],"monitoring":[158],"dynamic":[160],"environments.":[161]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-15T00:00:00"}
