Data mining to determine the causes of gender-based violence against women in ecuador

Abstract:

In this paper, we applied data mining to determine the causes of gender-based violence against women in Ecuador. We divided the original database into 30 subsets, according to the scopes in which violence occurs. We previously classified these subsets using six algorithms, namely Decision Trees(J48), Exhaustive CHAID, Neural Networks, Nearest Neighbors (IBk), Decision Tables, and Random Forests. The results of this classification showed a bias towards the majority class; for this reason, we applied the SMOTE Synthetic Minority Oversampling Technique to balance the classes and obtain better results. For the pbkp_redictions of the causes of violence, we used Exhaustive CHAID because our variables are mostly non-binary, and this algorithm allowed us to generate trees with more than two branches. IBk algorithm was the best at globally classifying the data, and Random Forests performed the best in …

Año de publicación:

2021

Keywords:

Fuente:

google