<p><span>Classification of information is a vague and difficult to explore area research, hence the emergence grouping techniques, often referred Clustering. It necessary differentiate between an unsupervised supervised classification. Clustering methods are numerous. Data partitioning hierarchization push use them in parametric form or not. Also, their influenced by algorithms prob...

Abstract This study uses detect breast cancer based on Random Forest (RF). It is crucial to diagnose the illness identify treatment solutions closely linked patient safety. Breast diagnosed using past medical records and various classification methods used in data mining fields today. Each technique performs differently depending input feature types model parameters. Neutral Networks have been ...

decision trees as one of the data mining techniques, is used in credit scoring of bank customers. the main problem is the construction of decision trees in that they can classify customers optimally. this paper proposes an appropriate model based on genetic algorithm for credit scoring of banks customers in order to offer credit facilities to each class. genetic algorithm can help in credit sco...

Learning models and related results depend on the quality of the input data. If raw data is not properly cleaned and structured, the results are tending to be incorrect. Therefore, discretization as one of the preprocessing techniques plays an important role in learning processes. The most important challenge in the discretization process is to reduce the number of features’ values. This operat...