Several studies have demonstrated the superior performance of ensemble classification algorithms, whereby multiple member classifiers are combined into one aggregated and powerful classification model, over single models. In this paper, two rotation-based ensemble classifiers are proposed as modeling techniques for customer churn prediction. In Rotation Forests, feature extraction is applied to...

Churning is the movement of customers from a company to another. For any company, being able to predict with some time which of their customers will churn is essential to take actions in order to retain them, and for this reason most sectors invest substantial effort in techniques for (semi)automatically predicting churning, and data mining and machine learning are among the techniques successf...

Employees are considered as the most valuable assets of any organization. Various policies have been introduced by HR professionals to create a good working environment for them, but still, rate employees quitting Technology Industry is quite high. Often reason behind their early attrition could be due company-related or personal issues, such No satisfaction at workplace, Fewer opportunities le...

Context: Effort-aware models, e.g., effort-aware bug prediction models aim to help practitioners identify and prioritize buggy software locations according to the effort involved with fixing the bugs. Since the effort of current bugs is not yet known and the effort of past bugs is typically not explicitly recorded, effort-aware bug prediction models are forced to use approximations, such as the...

In this paper, we use a partial least square (PLS) optimization method as a prediction model to estimate the churn probabilities of customers and as a control model after configuring optimization objective and constraints with relative management costs of controllable variables. In our experiment, we observe that while the training and test data sets are dramatically different in terms of churn...

At present situation, telecommunication department plays vital role in our day today human life. At the same time telecommunication area attains a rapid growth in very short period of years. Due to this fact, Telecom department is one of the senses deciding factor in world market. Because of this reason, this field turned out to be a most profitable area for investment. At the mean time competi...

In this paper, bagging and boosting techniques are proposed as performing tools for churn prediction. These methods consist of sequentially applying a classification algorithm to resampled or reweigthed versions of the data set. We apply these algorithms on a customer database of an anonymous U.S. wireless telecom company. Bagging is easy to put in practice and, as well as boosting, leads to a ...