This paper presents empirical evidence for five hypotheses about learning from large noisy domains: that trees built from very large training sets are larger and more accurate than trees built from even large subsets; that this increased accuracy is only in part due to the extra size of the trees; and that the extra training instances allow both better choices of attribute while building the tr...

Abstract Introduction: Myocardial Infarction, also known as heart attack, normally occurs due to such causes as smoking, family history, diabetes, and so on. It is recognized as one of the leading causes of death in the world. Therefore, the present study aimed to evaluate the performance of classification models in order to predict Myocardial Infarction, using a feature selection method tha...

Our investigation aims at interactively exploring the decision tree results obtained by the machine-learning algorithms like C4.5. We propose an interactive graphical environment using the new radial tree layout, zoom/pan techniques and some existing visualization methods like explorer-like, hierarchical visualization, interactive techniques to represent large decision trees in a graphical mode...

Over the past two decades, Machine Learning has become one of the mainstays of information technology. Machine learning is concerned with the development of algorithms and achieves optimization classification of attributes. Classification under the decision tree is the prediction approach of data mining techniques. In the decision tree, classification algorithm has the most common classifier to...

normal 0 false false false microsoftinternetexplorer4 background: the most common cancer among women is breast cancer and it has been blamed as the second leading cause of cancer death in women; so far many approaches have been used to analyze and detect benign and malignant forms of cancer and understanding the features involved in proteins expressed by various types of breast cancers is cruci...

Induction is the process of reasoning in which General rules are formulated based on limited observations of recurring phenomenal patterns. Decision tree learning is one of the most widely used and practical inductive methods, which represents the results in a tree scheme. Various decision tree algorithms have already been proposed, such as CLS, ID3, Assistant and C4.5. These algorithms suffer ...