Financial data processing method and device, computer equipment and storage medium

Financial data processing method and device, computer equipment and storage medium

The invention discloses a financial data processing method and device, computer equipment and a storage medium. The method comprises the steps of obtaining financial data from multiple data sources; determining missing data in the financial data; processing the financial data in a mode of combining...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: CHEN YAOWEN, HE HUAN, CHEN PENG, FAN ZUOJUN
Format: Patent
Sprache:chi ; eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:The invention discloses a financial data processing method and device, computer equipment and a storage medium. The method comprises the steps of obtaining financial data from multiple data sources; determining missing data in the financial data; processing the financial data in a mode of combining a KNN nearest neighbor filling algorithm and a maximum likelihood estimation algorithm, and determining a missing value corresponding to the missing data; determining abnormal data in the financial data; processing the financial data in a mode of combining a KNN nearest neighbor filling algorithm and a maximum likelihood estimation algorithm, and determining a normal value corresponding to the abnormal data; and filling abnormal data and missing data in the financial data according to the normal value and the missing value to obtain processed financial data. According to the embodiment of the invention, a mode of combining maximum likelihood estimation and KNN nearest neighbor filling is adopted to fill abnormal va