Electronic device and method for turnover rate prediction
AssigneePegatron Corporation
InventorsYuchi Liu, Tingan Jiang
Life of this patent
Estimating the term…
Abstract
An electronic device and a method for turnover rate prediction are provided, wherein the method includes: receiving human resource (HR) data; generating a feature dataset according to the HR data; inputting a first subset of the feature dataset to a first machine learning (ML) model to generate a first prediction; inputting a second subset of the feature dataset to a second ML model to generate a second prediction; and inputting the first prediction, the second prediction, and a third subset of the feature dataset to a third ML model to generate a first turnover rate prediction.
Claims20
An electronic device for turnover rate prediction, comprising:
- a transceiver;
- a storage medium, storing a plurality of modules;
- and
- a processor, coupled to the storage medium and the transceiver, and accessing and executing the plurality of modules, wherein the plurality of modules comprise:
- a data collecting module, receiving human resource data through the transceiver;
- a data mining module, generating a feature dataset according to the human resource data, wherein the feature dataset comprises a first subset, a second subset and a third subset;
- and
- a turnover rate estimation module, inputting the first subset to a first machine learning model to generate a first prediction, inputting a second subset to a second machine learning model to generate a second prediction, and inputting the first prediction, the second prediction and the third subset to a third machine learning model to generate a first turnover rate prediction.
A method for turnover rate prediction, comprising:
- receiving human resource data;
- generating a feature dataset according to the human resource data;
- inputting a first subset of the feature dataset to a first machine learning model to generate a first prediction;
- inputting a second subset of the feature dataset to a second machine learning model to generate a second prediction;
- and
- inputting the first prediction, the second prediction, and a third subset of the feature dataset to a third machine learning model to generate a first turnover rate prediction.
Dependencies are inferred from the claim text.