Explainable Muti-Label Classification of MBTI Types

arXiv:2405.02349v1 Announce Type: new
Abstract: In this study, we aim to identify the most effective machine learning model for accurately classifying Myers-Briggs Type Indicator (MBTI) types from Reddit posts and a Kaggle data set. We apply multi-label classification using the Binary Relevance method. We use Explainable Artificial Intelligence (XAI) approach to highlight the transparency and understandability of the process and result. To achieve this, we experiment with glass-box learning models, i.e. models designed for simplicity, transparency, and interpretability. We selected …

abstract aim apply artificial artificial intelligence arxiv binary classification cs.lg data data set explainable artificial intelligence highlight identify intelligence kaggle machine machine learning machine learning model reddit set study transparency type types xai