The term personality may be expressed in terms of the individual differences in characteristics pattern of thinking, feeling, and behavior. This work presents several machine learning techniques including Naive Bayes, Support Vector Machines, and Recurrent Neural Networks to predict people personality from text based on Myers-Briggs Type Indicator (MBTI). Furthermore, this project applies CRISP-DM, which stands for Cross-Industry Standard Process for Data Mining, to guide the learning process. Since, CRISP-DM is kind of iterative development, we have adopted it with agile methodology, which is a rapid iterative software development method, in order to reduce the development cycle to be minimal.
翻译:个人个性一词可以用个人在思维、感觉和行为特点模式方面的差异来表示,这项工作提出了几种机器学习技术,包括Nive Bayes、支持矢量机和经常性神经网络,以预测根据Myers-Briggs类型指标(MBTI)的文字中的人的个性。此外,这个项目还采用CRIPS-DM(即数据开采的跨行业标准进程)来指导学习过程。由于CRIPS-DM(CRIS-DM)是一种迭接式开发,我们采用了灵活的方法,这是一种快速迭接软件开发方法,目的是将开发周期减少到最低限度。