{"id":"W4230603371","doi":"10.1109/asonam.2016.7752356","title":"Spectral graph-based semi-supervised learning for imbalanced classes","year":2016,"lang":"en","type":"article","venue":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Artificial intelligence; Graph; Machine learning; Semi-supervised learning; Theoretical computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005813339,0.001363503,0.002177164,0.003297943,0.001310238,0.001496295,0.003660925,0.001972827,0.001556146],"category_scores_gemma":[0.01868667,0.0006174616,0.00109038,0.0024507,0.002122836,0.003747384,0.002638869,0.002575886,0.001048108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001561896,"about_ca_system_score_gemma":0.001596814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002640154,"about_ca_topic_score_gemma":0.004106691,"domain_scores_codex":[0.9964644,0.001385199,0.00021919,0.0007765487,0.0009779418,0.0001766611],"domain_scores_gemma":[0.9834065,0.009296712,0.001741951,0.002875673,0.002214395,0.000464842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004965506,0.0004243101,0.004706475,0.0002426766,0.000212574,0.0001739807,0.0004497651,0.5147952,0.004145843,0.02049989,0.009317901,0.4445348],"study_design_scores_gemma":[0.00000841245,0.00001652766,0.0001433363,0.000005579609,0.000004688239,0.0000197008,0.00002404352,0.9851754,0.0006114751,0.01368634,0.0002985302,0.000006036144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02164416,0.000208884,0.9753032,0.0002829425,0.00005383639,0.00009643523,0.0001458303,0.001574109,0.0006906344],"genre_scores_gemma":[0.4901861,0.0002384193,0.5044175,0.0004222189,0.0001806087,0.0004428652,0.001615557,0.0003890989,0.002107711],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005813339,"threshold_uncertainty_score":0.03074425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03140565970496059,"score_gpt":0.3221481992779155,"score_spread":0.2907425395729549,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}