{"id":"W2100286988","doi":"10.1109/tsmcb.2009.2038493","title":"Robust Classifiers for Data Reduced via Random Projections","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dimensionality reduction; Random projection; Curse of dimensionality; Pattern recognition (psychology); Random subspace method; Artificial intelligence; Classifier (UML); Subspace topology; Computer science; Robustness (evolution); k-nearest neighbors algorithm; Machine learning","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":[0.003447085,0.0008613417,0.001621534,0.001447603,0.0005954394,0.00163639,0.001040315,0.001396005,0.001683977],"category_scores_gemma":[0.0164737,0.000478917,0.0008726278,0.001282531,0.001420369,0.002426733,0.001771026,0.001994505,0.0008887757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009181079,"about_ca_system_score_gemma":0.001156312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001634731,"about_ca_topic_score_gemma":0.001151617,"domain_scores_codex":[0.9964479,0.0009236968,0.0001847217,0.0006552584,0.001591107,0.0001972731],"domain_scores_gemma":[0.9943715,0.003081898,0.0006965482,0.0008441941,0.0009192929,0.00008653398],"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":[0.0002732304,0.00007768866,0.0009123732,0.0002337679,0.000146317,0.0001928856,0.0001962739,0.4938033,0.01155963,0.1290922,0.005959683,0.3575526],"study_design_scores_gemma":[0.000008354977,0.00003820329,0.0002014266,0.00001370521,0.000009852533,0.00005976749,0.00001540698,0.970799,0.00238178,0.02490083,0.001558098,0.00001364644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006982588,0.000424904,0.9911755,0.0002353517,0.00004394775,0.00004281963,0.00006431949,0.0002575522,0.0007730166],"genre_scores_gemma":[0.3281986,0.001437272,0.664224,0.0003219753,0.000387361,0.0004334259,0.0007207707,0.0001221965,0.004154393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003447085,"threshold_uncertainty_score":0.01823014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05734560111877168,"score_gpt":0.2547730542609776,"score_spread":0.1974274531422059,"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."}}