Statements (49)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:technology
Data Analysis Method |
| gptkbp:benefit |
Scalability
Real-time Detection Reduced Human Intervention |
| gptkbp:challenge |
Interpretability
Concept Drift Data Quality Issues High False Positive Rate Imbalanced Data |
| gptkbp:goal |
Alert on Abnormal Events
Detect Unusual Patterns Identify Outliers |
| https://www.w3.org/2000/01/rdf-schema#label |
Automated Anomaly Detection
|
| gptkbp:input |
gptkb:Medical_Records
Sensor Data Network Logs Transaction Data |
| gptkbp:method |
gptkb:Unsupervised_Learning
gptkb:Neural_Networks gptkb:Support_Vector_Machines Time Series Analysis Statistical Methods Clustering Supervised Learning Autoencoders Semi-supervised Learning Isolation Forest |
| gptkbp:output |
gptkb:Alert
Visualization Classification Anomaly Score |
| gptkbp:relatedStandard |
gptkb:ISO/IEC_27001
gptkb:NIST_SP_800-94 |
| gptkbp:relatedTo |
gptkb:Machine_Learning
gptkb:artificial_intelligence gptkb:Pattern_Recognition gptkb:Big_Data_Analytics Data Mining Statistical Analysis Outlier Detection |
| gptkbp:usedIn |
gptkb:Network_Monitoring
Finance Cybersecurity Healthcare Analytics Fraud Detection Industrial Monitoring |
| gptkbp:bfsParent |
gptkb:AAD
|
| gptkbp:bfsLayer |
7
|