{"id":"W2276557110","doi":"10.1109/wi-iat.2015.189","title":"Stock Price Prediction in Undirected Graphs Using a Structural Support Vector Machine","year":2015,"lang":"en","type":"article","venue":"","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Support vector machine; Computer science; Graph; Stock market; Artificial intelligence; Analytics; Undirected graph; Exploit; Data mining; Machine learning; Theoretical computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004645142,0.000498027,0.0004051404,0.001020286,0.0002010948,0.0005120873,0.0007773064,0.0005882159,0.000914781],"category_scores_gemma":[0.00295205,0.0002742363,0.0004928511,0.000788776,0.0003002978,0.0009811373,0.0004256614,0.0006536134,0.0002684232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006328241,"about_ca_system_score_gemma":0.00050179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007955557,"about_ca_topic_score_gemma":0.009560473,"domain_scores_codex":[0.9998031,0.00005574834,0.00001036315,0.00005787663,0.00004382795,0.0000290563],"domain_scores_gemma":[0.9987946,0.0007007734,0.0001574168,0.00009973152,0.0001983148,0.00004919218],"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":[0.00006401267,0.0000545912,0.002880279,0.00001636431,0.00001995908,0.0000588276,0.0000198851,0.9515103,0.001401685,0.001881135,0.0005043353,0.04158867],"study_design_scores_gemma":[0.000001156149,0.000006287581,0.0001170559,5.756164e-7,8.804147e-7,0.000002313561,0.000001647367,0.9989271,0.0001330222,0.0007843786,0.00002492221,7.2333e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4428679,0.0001463612,0.552737,0.0004653763,0.00003731625,0.00005962284,0.0004139178,0.001294,0.001978581],"genre_scores_gemma":[0.9341645,0.00007324972,0.06412643,0.00004552141,0.00001545334,0.00003234771,0.0004934135,0.00002216758,0.001026995],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007955557,"threshold_uncertainty_score":0.01581848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2169303873634565,"score_gpt":0.4304158469813024,"score_spread":0.213485459617846,"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."}}