{"id":"W2082663547","doi":"10.5430/air.v1n2p117","title":"Adaboost and SVM based cybercrime detection and prevention model","year":2012,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Computer science; AdaBoost; Cybercrime; Machine learning; Executable; Artificial intelligence; Classifier (UML); Data mining; Software; Pattern recognition (psychology); The Internet; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001628077,0.000866636,0.001377147,0.001629397,0.0005338851,0.001187848,0.001645759,0.001570271,0.001959543],"category_scores_gemma":[0.002386965,0.0003870613,0.0008291226,0.0009257963,0.0004429965,0.001449924,0.0003767542,0.001348804,0.0007204888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009533918,"about_ca_system_score_gemma":0.001003835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005617815,"about_ca_topic_score_gemma":0.003829912,"domain_scores_codex":[0.9990721,0.0002484778,0.00006290722,0.0001897768,0.0002838534,0.0001429619],"domain_scores_gemma":[0.9986334,0.0005351797,0.000145959,0.0000597191,0.0005563877,0.00006929902],"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":[0.0007050146,0.001330186,0.01226671,0.0003194827,0.000286266,0.0001570184,0.0001016765,0.5697447,0.004611108,0.005177953,0.006960628,0.3983393],"study_design_scores_gemma":[0.00001019439,0.00008220657,0.0009375733,0.00001056441,0.00001608001,0.00004059094,0.00001503798,0.9964126,0.0009327431,0.0009466241,0.0005861018,0.000009738352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.162378,0.001965977,0.8258319,0.00146163,0.0005459844,0.0002981958,0.0003407484,0.001959625,0.005217957],"genre_scores_gemma":[0.8354502,0.0006560807,0.1543408,0.000338255,0.0002257314,0.0002923623,0.0004588526,0.00005392338,0.008183676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005617815,"threshold_uncertainty_score":0.01117027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2550317435761351,"score_gpt":0.417311105255372,"score_spread":0.1622793616792368,"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."}}