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Machine Learning Approach to Personality Type Prediction Based on the Myers–Briggs Type Indicator?

机译:基于Myers-Briggs类型指示器的人格类型预测机器学习方法?

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Neuro Linguistic Programming (NLP) is a collection of techniques for personality development. Meta programmes, which are habitual ways of inputting, sorting and filtering the information found in the world around us, are a vital factor in NLP. Differences in meta programmes result in significant differences in behaviour from one person to another. Personality types can be recognized through utilizing and analysing meta programmes. There are different methods to predict personality types based on meta programmes. The Myers–Briggs Type Indicator~(?) (MBTI) is currently considered as one of the most popular and reliable methods. In this study, a new machine learning method has been developed for personality type prediction based on the MBTI. The performance of the new methodology presented in this study has been compared to other existing methods and the results show better accuracy and reliability. The results of this study can assist NLP practitioners and psychologists in regards to identification of personality types and associated cognitive processes.
机译:神经语言编程(NLP)是一个人格开发技术的集合。元计划是习惯性的输入,分类和过滤我们周围世界各地的信息的习惯性方式,是NLP的重要因素。元计划的差异导致一个人到另一个人的行为的显着差异。可以通过利用和分析元程序来识别人格类型。存在基于元程序预测人格类型的不同方法。 Myers-Briggs类型指示器〜(?)(MBTI)目前被认为是最受欢迎和可靠的方法之一。在本研究中,基于MBTI的个性类型预测开发了一种新的机器学习方法。本研究中呈现的新方法的性能已经与其他现有方法进行了比较,结果表明了更好的准确性和可靠性。本研究的结果可以帮助NLP从业者和心理学家在识别人格类型和相关的认知过程方面。

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