internet applications spreading and its high usage popularity result insignificant increasing of cyber-attacks. consequently, network security has becomea matter of importance and several methods have been developed for these attacks.for this purpose, intrusion detection systems (ids) are being used to monitor theattacks occurred on computer networks. data mining techniques, machinelearning, ne...

background : breast cancer survival has been analyzed by many standard data mining algorithms. a group of these algorithms belonged to the decision tree category. ability of the decision tree algorithms in terms of visualizing and formulating of hidden patterns among study variables were main reasons to apply an algorithm from the decision tree category in the current study that has not studied...

When using machine learning to predict a class with continuous numeric value, there are several issues. Only few machine-learning approaches capable of doing so, but it remains one the most difficult jobs do. In this paper, we show how use M5 Model Tree, an approach that can handle data. This method is stepwise procedure employs linear functions at leaf nodes any created decision tree inducer (...

Reliable estimations of sediment yields are very important for investigations river morphology and water resources management. Nowadays, soft computing methods helpful famous regarding the accurate estimation loads. The present study checked applicability radial M5 tree (RM5Tree) model to accurately estimate using daily inputs snow cover fraction, air temperature, evapotranspiration effective r...

due to the high penetration of wind farms in the networks, they can have a significant role in the control of power systems. in this paper, wind farms (wfs) are used to improve the static security margins of the power system. generation rescheduling is one of the remedies to improve the static security margins of the power system. in this paper, the generation rescheduling is presented based on...

Predicting a class with continuous numeric value encounters many problems when applying machine learning to the data. Only few machine-learning techniques can do this, but it is still considered one of most complex tasks perform. In this study, we demonstrate called M5 Model Tree, which handle This technique stepwise algorithm and uses linear functions at leaf nodes any decision tree inducer (l...