Prediction of Couple Relationship in the Covid-19 Era Using Correlation Based Feature Selection and Machine Learning

As coronavirus disease progressed, most societies experienced an increase in divorce rates due to dissatisfaction, incompatibility, and turmoil in couples' relationships. One of the effective factors in a successful marriage is the realistic expectation of marriage that examining the factors of a successful marriage is an important step to achieve this aim. In this regard, we investigated the effective factors in a successful marriage or divorce of couples using machine learning algorithms. To predict the type of couple relationship, this study designed a standard questionnaire with 54 questions based on Guttman's couple therapy questionnaire in the Kaggle database. The purpose of this questionnaire is to determine the survival of the relationship using the analysis of 170 couples' responses. The designed questionnaire was distributed among 33 Iranian families and the type of relationship between couples was predicted using machine learning algorithms. Also, the effective features of the relationship between couples in Iranian culture in this study were extracted with the help of Pearson correlation coefficient and with the effective features in another study that was performed on people with different cultures; Compared and the results showed that culture change can change some of the effective characteristics. Experimental results demonstrated that the effective factors in predicting a person's divorce or marriage are: 1- Intimacy between couples and 2- Silence and suppression of anger in discussions and disputes. Among the examined machine learning algorithms, the decision tree and naive Bayes have shown the highest efficiency with 100% accuracy.