Development of a classification model to predict if the student has internet connectivity at home
Developing a classification model for predicting if the student has internet connectivity at home or not.
The dataset contains 649 observations and 33 variables. The dataset has two kinds of information Personal information: Age, Sex, Family size, Parent(s) Job and Educational Background, Parent(s) Cohabitation status, Health, Romantic Activity, Quality of family relationship, Presence of Romantic relationship, alcohol consumption, free time, extracurricular activities. School and Education information: School, Reason to choose school, study time, number of past class failures, number of absences, family and other educational support, grades in first, second and third periods.
The data source can be found here.