The paper discusses the results obtained to predict reinforcement in singly reinforced beam using Neural Net (NN), Support Vector Machines (SVM’s) and Tree Based Models. Major advantage of SVM’s over NN is of minimizing a bound on the generalization error of model rather than minimizing a bound on mean square error over the data set as done in NN. Tree Based approach divides the problem into a ...

classifying customers using data mining algorithms, enables banks to keep old customers loyality while attracting new ones. using decision tree as a data mining technique, we can optimize customer classification provided that the appropriate decision tree is selected. in this article we have presented an appropriate model to classify customers who use internet banking service. the model is deve...

Partial 1-trees are undirected graphs of treewidth at most one. Similarly, partial 1-DAGs are directed graphs of KellyWidth at most two. It is well-known that an undirected graph is a partial 1-tree if and only if it has no K3 minor. In this paper, we generalize this characterization to partial 1-DAGs. We show that partial 1-DAGs are characterized by three forbidden directed minors, K3, N4 and M5.

background: length of stay is one of the most important indicators in assessing hospital performance. a shorter stay can reduce the costs per discharge and shift care from inpatient to less expensive post-acute settings. it can lead to a greater readmission rate, better resource management, and more efficient services. objective: this study aimed to identify the factors influencing length of ho...

background : the data related to patients often have very useful information that can help us to resolve a lot of problems and difficulties in different areas. this study was performed to present a model-based data mining to predict lung cancer in 2014. methods : in this exploratory and modeling study, information was collected by two methods: library and field methods. all gathered variables w...