{"id":"W1558411928","doi":"10.1007/978-3-642-30721-8_2","title":"Unsupervised Feature Selection for Spherical Data Modeling: Application to Image-Based Spam Filtering","year":2012,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Artificial intelligence; Computer science; Pattern recognition (psychology); Feature selection; Cluster analysis; Generalization; Support vector machine; Feature (linguistics); Relevance (law); Kernel (algebra); Statistical model; Maximization; Machine learning; Image (mathematics); Data mining; Mathematics","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":[0.00146109,0.0008753455,0.001411377,0.0009243362,0.0004379095,0.0008882559,0.001015181,0.0009916977,0.001064235],"category_scores_gemma":[0.004910361,0.0003976092,0.001132942,0.00170943,0.0004747275,0.000905516,0.0008986318,0.0009982184,0.0007474679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005152421,"about_ca_system_score_gemma":0.0005845813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002830831,"about_ca_topic_score_gemma":0.002793232,"domain_scores_codex":[0.9995418,0.0001796413,0.00003219544,0.00007844587,0.0001353317,0.00003259912],"domain_scores_gemma":[0.9984103,0.0009422664,0.0001077106,0.0001709805,0.0003364747,0.0000321747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001996789,0.0001380525,0.00127606,0.0002435174,0.0001410274,0.0001761999,0.0002096058,0.3433936,0.02811759,0.0242372,0.008257673,0.5936098],"study_design_scores_gemma":[0.000002895324,0.00001337744,0.0001746476,0.000002888936,0.000007995031,0.00004298774,0.00000700421,0.9934227,0.001900372,0.003725286,0.0006929719,0.000006921592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002100618,0.0001284806,0.9973195,0.00004227324,0.00001272664,0.000009115222,0.0000180851,0.0002409126,0.0001282799],"genre_scores_gemma":[0.1573138,0.0008067649,0.8383603,0.00009987459,0.0001730289,0.0001549073,0.0003447802,0.0003144659,0.002432166],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002830831,"threshold_uncertainty_score":0.007727087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0817836262420554,"score_gpt":0.3271467609406397,"score_spread":0.2453631346985843,"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."}}