Ngo, F. T., Govindu, R., & Agarwal, A. (2015). Assessing the Predictive Utility of Logistic Regression, Classification and Regression Tree, Chi-Squared Automatic Interaction Detection, and Neural Network Models in Predicting Inmate Misconduct. American journal of criminal justice, 40(1), 47-74. doi:10.1007/s12103-014-9246-6
Cita Chicago Style (17a ed.)Ngo, Fawn T., Ramakrishna Govindu, y Anurag Agarwal. "Assessing the Predictive Utility of Logistic Regression, Classification and Regression Tree, Chi-Squared Automatic Interaction Detection, and Neural Network Models in Predicting Inmate Misconduct." American Journal of Criminal Justice 40, no. 1 (2015): 47-74. https://doi.org/10.1007/s12103-014-9246-6.
Cita MLA (9a ed.)Ngo, Fawn T., et al. "Assessing the Predictive Utility of Logistic Regression, Classification and Regression Tree, Chi-Squared Automatic Interaction Detection, and Neural Network Models in Predicting Inmate Misconduct." American Journal of Criminal Justice, vol. 40, no. 1, 2015, pp. 47-74, https://doi.org/10.1007/s12103-014-9246-6.
