{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002827586,0.0004165963,0.0004504664,0.0002264403,0.000293665,0.0002275452,0.0004302118,0.0003410897,0.0000298885],"category_scores_gemma":[0.00001101028,0.0004244713,0.0001196138,0.0002093591,0.000179871,0.0001455077,0.000008130252,0.0006238074,0.00002886156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004044773,"about_ca_system_score_gemma":0.0000370287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001641233,"about_ca_topic_score_gemma":0.0003807997,"domain_scores_codex":[0.9980125,0.00006080545,0.0005540774,0.0006153975,0.0002692835,0.0004879263],"domain_scores_gemma":[0.9981263,0.000193456,0.00009618804,0.001219921,0.000134717,0.0002293671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009232045,0.001572885,0.0001255315,0.001148539,0.002693709,0.00006317143,0.002779093,0.3183793,0.3212406,0.004835162,0.2118803,0.1343585],"study_design_scores_gemma":[0.002157382,0.000254398,0.00005536855,0.000242287,0.0003873444,0.0001731956,0.000209204,0.8098303,0.04465819,0.00028596,0.1407669,0.0009794378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05546995,0.0003580776,0.9281477,0.0001329576,0.006341571,0.001991465,0.0002968105,0.001366558,0.005894844],"genre_scores_gemma":[0.9932333,0.0003760871,0.003455047,0.00004056459,0.0003903391,0.0002642942,0.00004784728,0.0001282716,0.002064206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9377634,"threshold_uncertainty_score":0.9998207,"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."}}