首页> 外文期刊>Computers, informatics, nursing: CIN >Predicting Nurses' Intention to Quit With a Support Vector Machine: A New Approach to Set up an Early Warning Mechanism in Human Resource Management.
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Predicting Nurses' Intention to Quit With a Support Vector Machine: A New Approach to Set up an Early Warning Mechanism in Human Resource Management.

机译:使用支持向量机预测护士的退出意愿:在人力资源管理中建立预警机制的新方法。

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摘要

This project developed a Support Vector Machine for predicting nurses' intention to quit, using working motivation, job satisfaction, and stress levels as predictors. This study was conducted in three hospitals located in southern Taiwan. The target population was all nurses (389 valid cases). For cross-validation, we randomly split cases into four groups of approximately equal sizes, and performed four training runs. After the training, the average percentage of misclassification on the training data was 0.86, while that on the testing data was 10.8, resulting in predictions with 89.2% accuracy. This Support Vector Machine can predict nurses' intention to quit, without asking these nurses whether they have an intention to quit.
机译:该项目开发了一种支持向量机,用于以工作动机,工作满意度和压力水平作为预测因素来预测护士的离职意愿。这项研究是在台湾南部的三所医院进行的。目标人群是所有护士(389名有效病例)。为了进行交叉验证,我们将案例随机分为大小相等的四组,并进行了四次训练。训练后,训练数据上的错误分类的平均百分比为0.86,而测试数据上的错误分类的平均百分比为10.8,因此预测的准确性为89.2%。该支持向量机可以预测护士的辞职意愿,而无需询问这些护士是否有辞职意愿。

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