A Heuristically Perturbation of Dataset to Achieve a Diverse Ensemble of Classifiers

Abstract

Ensemble methods like Bagging and Boosting which combine the decisions of multiple hypotheses are among the strongest existing machine learning methods. The diversity of the members of an ensemble is known to be an important factor in determining its generalization error. We present a new method for generating ensembles, named CDEBMTE (Creation of Diverse Ensemble Based on Manipulation of Training Examples), that directly constructs diverse hypotheses using manipulation of training examples in three ways: (1) sub-sampling training examples, (2) decreasing/increasing errorprone training examples and (3) decreasing/increasing neighbor samples of error-prone training examples.The technique is a simple, general meta-learner that can use any strong learner as a base classifier to build diverse committees. Experimental results using two well-known classifiers (1) decision-tree induction and (2) multilayer perceptron as two base learners demonstrate that this approach consistently achieves higher predictive accuracy than both the base classifier, Adaboost and Bagging. CDEBMTE also outperforms Adaboost more prominent when training data size is becomes larger.We propose to show that CDEBMTE can be effectively used to achieve higher accuracy and to obtain better class membership probability estimates.Experimental results using two well-known classifiers as two base learners demonstrate that this approach consistently achieves higher predictive accuracy than both the base classifier, Adaboost and Bagging. CDEBMTE also outperforms Adaboost more prominent when training data size is becomes larger.

The assessment of the associated factors of Emotional divorce among Iranian couples during the Covid19 Pandemic: A descriptive study

“…Overall, this study shows increasing of the chance of emotional divorce by family chosen spouses. This nding is the same as the results of a study that worked on the socio-demographic factors affecting divorce, according to which factors related to parents and family structure can be predictors of marital divorce (25). Therefore, it seems family chosen spouse can be a sign of the type of family structure and lack of decision-making independence, where the combination of these factors will increase marital con icts and subsequently the chances of emotional divorce.…”