IDENTIFYING AND OPTIMIZING SKILL SCARCITY MACHINE LEARNING ALGORITHMS

A data set including at least skills data, recruiting data, compensation data, organization structure data can be received. A first training set can be created by cleaning and integrating the data set. A first machine learning model can be trained to predict skill scarcity associated with a skill, g...

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Bibliographische Detailangaben
Hauptverfasser:	LaMoreaux, Nickle Jaclyn, Midkiff, Karen, Li, Ying, Low, Yvonne Cai Feng, Daly, Joanna M, Sheopuri, Anshul, Stachura, Thomas A
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:	A data set including at least skills data, recruiting data, compensation data, organization structure data can be received. A first training set can be created by cleaning and integrating the data set. A first machine learning model can be trained to predict skill scarcity associated with a skill, geography and organization using the first training set. A second training set can be created by selecting a subset of the first training set based on a local subject matter expert's input with respect to the trained first machine learning model's performance. The first machine learning model can be refined by retraining the first machine learning model using the second training set, the machine learning model refined to predict the skill scarcity associated with the skill, geography and organization within a locality associated with the local subject matter expert.