MACHINE LEARNING SYSTEM TO IDENTIFY AND OPTIMIZE FEATURES BASED ON HISTORICAL DATA, KNOWN PATTERNS, OR EMERGING PATTERNS

MACHINE LEARNING SYSTEM TO IDENTIFY AND OPTIMIZE FEATURES BASED ON HISTORICAL DATA, KNOWN PATTERNS, OR EMERGING PATTERNS

Machine learning models, semantic networks, adaptive systems, artificial neural networks, convolutional neural networks, and other forms of knowledge processing systems are disclosed. An ensemble machine learning system is coupled to a graph module storing a graph structure, wherein a collection of...

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Bibliographische Detailangaben
Hauptverfasser: Payne, Margaret A, Morris, Ronnie J, Edkin, Lorraine C, Filliben, Joel, Sims, Scott A, Widmann, Craig Douglas, Pusey-Conlin, Dana M, Kursun, Eren
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:Machine learning models, semantic networks, adaptive systems, artificial neural networks, convolutional neural networks, and other forms of knowledge processing systems are disclosed. An ensemble machine learning system is coupled to a graph module storing a graph structure, wherein a collection of entities and the relationships between those entities forms nodes and connection arcs between the various nodes. A hotfile module and hotfile propagation engine coordinate with the graph module or may be subsumed within the graph module, and implement the various hot file functionality generated by the machine learning systems.