نتایج جستجو برای: Ensemble of Decision Tree
تعداد نتایج: 21209322 فیلتر نتایج به سال:
in this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. then, for optimizing the initial feature vector, a genetic algorithm is proposed. some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and k-nearest neig...
In this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. Then, for optimizing the initial feature vector, a genetic algorithm is proposed. Some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and K-nearest neig...
Due to the growth of the aging phenomenon, the use of intelligent systems technology to monitor daily activities, which leads to a reduction in the costs for health care of the elderly, has received much attention. Considering that each person's daily activities are related to his/her moods, thus, the relationship can be modeled using intelligent decision-making algorithms such as machine learn...
Due to the rise of technology, the possibility of fraud in different areas such as banking has been increased. Credit card fraud is a crucial problem in banking and its danger is over increasing. This paper proposes an advanced data mining method, considering both feature selection and decision cost for accuracy enhancement of credit card fraud detection. After selecting the best and most effec...
Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...
The aim of this study is to predict and model flood hazard in the city of Nowshahr, Mazandaran province using machine learning models. The criteria and indicators affecting flood hazard were identified based on the review of resources, and then the indicators were converted into rasters in ArcGIS environment, and finally standardized by fuzzy method for use in the models. K-nearest neighbor ...
due to extraordinary large amount of information and daily sharp increasing claimant for ui benefits and because of serious constraint of financial barriers, the importance of handling fraud detection in order to discover, control and predict fraudulent claims is inevitable. we use the most appropriate data mining methodology, methods, techniques and tools to extract knowledge or insights from ...
abstract nowadays, the science of decision making has been paid to more attention due to the complexity of the problems of suppliers selection. as known, one of the efficient tools in economic and human resources development is the extension of communication networks in developing countries. so, the proper selection of suppliers of tc equipments is of concern very much. in this study, a ...
Decision tree is with good comprehensibility while neural network ensemble is with strong generalization ability. In this paper, these merits are integrated into a novel decision tree algorithm NeC4.5. This algorithm trains a neural network ensemble at first. Then, the trained ensemble is employed to generate a new training set through replacing the desired class labels of the original training...
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