{"id":"https://openalex.org/W7213301609","doi":"https://doi.org/10.26434/chemrxiv.15008808/v1","title":"Tree-Based Classification of Functional Groups from IR Spectra: Feature Importance Corroborates Quantum-Chemical Fragment Frequencies","display_name":"Tree-Based Classification of Functional Groups from IR Spectra: Feature Importance Corroborates Quantum-Chemical Fragment Frequencies","publication_year":2026,"publication_date":"2026-09-14","ids":{"openalex":"https://openalex.org/W7213301609","doi":"https://doi.org/10.26434/chemrxiv.15008808/v1"},"language":"en","primary_location":{"id":"doi:10.26434/chemrxiv.15008808/v1","doi":"https://doi.org/10.26434/chemrxiv.15008808/v1","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15008808/v1","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15008808/v1","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15008808/v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028678356","display_name":"Muhammad Khari Secario","orcid":"https://orcid.org/0000-0003-1271-3588","observed_orcids":["https://orcid.org/0000-0003-1271-3588"]},"institutions":[{"id":"https://openalex.org/I173093425","display_name":"Chang Gung University","ror":"https://ror.org/00d80zx46","country_code":"TW","type":"education","lineage":["https://openalex.org/I173093425"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Muhammad Khari Secario","raw_affiliation_strings":["Chang Gung University","Department of Chemical and Materials Engineering"],"raw_orcid":"https://orcid.org/0000-0003-1271-3588","affiliations":[{"raw_affiliation_string":"Chang Gung University","institution_ids":["https://openalex.org/I173093425"]},{"raw_affiliation_string":"Department of Chemical and Materials Engineering","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091583430","display_name":"Shingjiang Jessie Lue","orcid":"https://orcid.org/0000-0003-1950-8093","observed_orcids":["https://orcid.org/0000-0003-1950-8093"]},"institutions":[{"id":"https://openalex.org/I12213908","display_name":"Ming Chi University of Technology","ror":"https://ror.org/04xgh4d03","country_code":"TW","type":"education","lineage":["https://openalex.org/I12213908"]},{"id":"https://openalex.org/I173093425","display_name":"Chang Gung University","ror":"https://ror.org/00d80zx46","country_code":"TW","type":"education","lineage":["https://openalex.org/I173093425"]},{"id":"https://openalex.org/I3020100970","display_name":"Chang Gung Memorial Hospital","ror":"https://ror.org/02verss31","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I3020100970"]},{"id":"https://openalex.org/I4210116208","display_name":"Linkou Chang Gung Memorial Hospital","ror":"https://ror.org/02dnn6q67","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I3020100970","https://openalex.org/I4210116208"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shingjiang Jessie Lue","raw_affiliation_strings":["Chang Gung Memorial Hospital","Chang Gung University","Department of Chemical and Materials Engineering","Department of Pediatrics","Department of Safety, Health and Environment Engineering","Ming-Chi University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chang Gung Memorial Hospital","institution_ids":["https://openalex.org/I3020100970","https://openalex.org/I4210116208"]},{"raw_affiliation_string":"Chang Gung University","institution_ids":["https://openalex.org/I173093425"]},{"raw_affiliation_string":"Department of Chemical and Materials Engineering","institution_ids":[]},{"raw_affiliation_string":"Department of Pediatrics","institution_ids":[]},{"raw_affiliation_string":"Department of Safety, Health and Environment Engineering","institution_ids":[]},{"raw_affiliation_string":"Ming-Chi University of Technology","institution_ids":["https://openalex.org/I12213908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.009700000286102295,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/functional-group-classification","display_name":"functional group classification","score":0.8339999914169312},{"id":"https://openalex.org/keywords/infrared-spectra","display_name":"infrared spectra","score":0.7419999837875366},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8889999985694885},{"id":"https://openalex.org/keywords/feature-importance","display_name":"feature importance","score":0.8019999861717224},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.8100000023841858},{"id":"https://openalex.org/keywords/threshold-adjustment","display_name":"threshold adjustment","score":0.6600000262260437},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.6320000290870667},{"id":"https://openalex.org/keywords/ftir-spectroscopy","display_name":"FTIR spectroscopy","score":0.5149999856948853},{"id":"https://openalex.org/keywords/compound-identification","display_name":"compound identification","score":0.38600000739097595}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6287999749183655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5605999827384949},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5446000099182129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5011000037193298},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44699999690055847},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C153642686","wikidata":"https://www.wikidata.org/wiki/Q70906","display_name":"Infrared spectroscopy","level":2,"score":0.4207000136375427},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.4194999933242798},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.40070000290870667},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.38839998841285706},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3384999930858612},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3382999897003174},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3359000086784363},{"id":"https://openalex.org/C43571822","wikidata":"https://www.wikidata.org/wiki/Q599037","display_name":"Near-infrared spectroscopy","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C4839761","wikidata":"https://www.wikidata.org/wiki/Q212111","display_name":"Spectral line","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C2776235265","wikidata":"https://www.wikidata.org/wiki/Q18392052","display_name":"Fragment (logic)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C184389593","wikidata":"https://www.wikidata.org/wiki/Q603159","display_name":"Curve fitting","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.2694999873638153},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.26434/chemrxiv.15008808/v1","doi":"https://doi.org/10.26434/chemrxiv.15008808/v1","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15008808/v1","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15008808/v1","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.26434/chemrxiv.15008808/v1","doi":"https://doi.org/10.26434/chemrxiv.15008808/v1","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15008808/v1","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15008808/v1","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2558515332","display_name":"Development of Novel Nano-Structured Electrolyte Membranes and Electrode Materials for Direct Alkaline Ammonia Fuel Cells","funder_award_id":"NSTC114-2221-E182-052","funder_id":"https://openalex.org/F2461203286","funder_display_name":"National Science and Technology Council"}],"funders":[{"id":"https://openalex.org/F2461203286","display_name":"National Science and Technology Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7213301609.pdf","grobid_xml":"https://content.openalex.org/works/W7213301609.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1966716734","https://openalex.org/W1972295548","https://openalex.org/W2018424207","https://openalex.org/W2033858268","https://openalex.org/W2034558631","https://openalex.org/W2057398410","https://openalex.org/W2067718414","https://openalex.org/W2079073250","https://openalex.org/W2118978333","https://openalex.org/W2164330572","https://openalex.org/W2174652798","https://openalex.org/W2898361048","https://openalex.org/W2999309192","https://openalex.org/W3047885487","https://openalex.org/W3099466918","https://openalex.org/W3126232929","https://openalex.org/W3137237498","https://openalex.org/W3208302614","https://openalex.org/W3215724575","https://openalex.org/W4283712422","https://openalex.org/W4321214126","https://openalex.org/W4324118152","https://openalex.org/W4360992523","https://openalex.org/W4381542508","https://openalex.org/W4385476447","https://openalex.org/W4389538269","https://openalex.org/W4392805205","https://openalex.org/W4398160596","https://openalex.org/W4402128718","https://openalex.org/W4404141682","https://openalex.org/W4404435697","https://openalex.org/W4409666631","https://openalex.org/W4410707435","https://openalex.org/W4414553254","https://openalex.org/W7161161234","https://openalex.org/W7161397514"],"related_works":["https://openalex.org/W2790915970","https://openalex.org/W3137237498","https://openalex.org/W4385476447","https://openalex.org/W4416982086","https://openalex.org/W7149018446","https://openalex.org/W2314260885","https://openalex.org/W3047885487","https://openalex.org/W4414286526","https://openalex.org/W4408614196","https://openalex.org/W4391320745"],"abstract_inverted_index":{"Fourier-transform":[0],"infrared":[1,56],"(FTIR)":[2],"spectroscopy":[3],"is":[4],"a":[5,36,129,163],"widely":[6],"used":[7],"analytical":[8],"technique":[9],"for":[10,28,169],"identifying":[11],"functional":[12,51],"groups":[13,52],"in":[14,132],"chemical":[15,158],"compounds,":[16],"but":[17],"its":[18],"interpretation":[19],"remains":[20],"labor-intensive":[21],"and":[22,85,112,152,174],"reliant":[23],"on":[24],"expert":[25],"knowledge,":[26],"especially":[27],"complex":[29],"or":[30],"multicomponent":[31],"samples.":[32],"This":[33],"study":[34],"presents":[35],"tree-based":[37],"Random":[38],"Forest":[39],"(RF)":[40],"machine-learning":[41],"framework,":[42],"successfully":[43],"developed":[44],"to":[45,62,128],"predict":[46],"the":[47,68,92,116,140],"presence":[48],"of":[49],"specific":[50],"(FGs)":[53],"from":[54,139],"an":[55],"spectra":[57,151],"database.":[58],"Stratification":[59],"was":[60],"employed":[61],"address":[63],"positive":[64],"class":[65],"imbalance,":[66],"maintaining":[67],"F1-score":[69],"drop":[70],"under":[71,115],"12%":[72],"across":[73],"models.":[74],"All":[75],"models":[76,142],"achieved":[77],"strong":[78,144],"overall":[79],"performance,":[80,99,125],"with":[81,147,156,167],"accuracy,":[82],"F1-score,":[83],"ROC-AUC,":[84],"out-of-bag":[86],"(OOB)":[87],"scores":[88],"exceeding":[89],"0.8.":[90],"Of":[91],"46":[93],"FGs":[94],"modeled,":[95],"43":[96],"demonstrated":[97],"acceptable":[98],"while":[100],"only":[101],"three":[102],"underperformed,":[103],"as":[104],"categorized":[105],"by":[106],"their":[107],"Matthews":[108],"correlation":[109],"coefficient":[110],"(MCC)":[111],"precision-recall":[113],"area":[114],"curve":[117],"(PR-AUC)":[118],"scores.":[119],"Threshold":[120],"tuning":[121],"further":[122],"improved":[123],"model":[124],"yielding":[126],"up":[127],"9%":[130],"increase":[131],"MCC":[133],"score.":[134],"Finally,":[135],"feature":[136],"importance":[137],"extracted":[138],"trained":[141],"exhibited":[143],"interpretability,":[145],"correlating":[146],"theoretically":[148],"predicted":[149],"IR":[150],"bridging":[153],"experimental":[154],"data":[155],"theoretical":[157],"significance.":[159],"These":[160],"results":[161],"establish":[162],"robust,":[164],"interpretable":[165],"framework":[166],"potential":[168],"integration":[170],"into":[171],"intelligent":[172],"monitoring":[173],"process":[175],"optimization":[176],"systems.":[177]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-09-16T00:00:00"}