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During the past years various fraud detection techniques were proposed and used to reduce fraudulent activities. Selection an optimal fraud detection model becomes keen area of interest for researchers in the field of anomaly detection. Methods and tools for fraud detection model selection which were used in the literature used a limited no of model selection criteria for finding the detection of...
India is leading all nations in number of maternal deaths. To reduce the national maternal mortality rate the government is doing efforts and has introduced many schemes like JSSK and JSY to create awareness towards the institutional deliveries and to benefit the rural women economically. Despite such programmatic efforts by Indian government the goal to achieve maternal mortality less than 100 per...
In bioinformatics research, the biggest challenge is to extract information from large datasets according to ones interestingness criteria. For research in genetics the DNA microarray technology provides better results in comparison with the standard approach as it has computerized the parallel analysis of thousands of genes for monitoring expression levels of genes. Thus, for the biologists the challenge...
The weight is assigned to all edges of graph according to a uniform policy and focus is on the leaves nodes of the Spanning Tree of Control Flow Graph of Program. If all leaves nodes of Spanning tree are covered by the test cases, then number of test cases required or testing the program can be reduced to great extent. Further the spanning tree is based on the concept of maximum spanning tree of CFG...
This paper is based on Swine Influenza Models Based Optimization (SIMBO) natural computing technique which is used to automatic software test data generation. The concept of dominance relation between nodes has been used as fitness function in this paper. Finally, the results in the paper show the effectiveness of SIMBO techniques as compare to Particle Swarm Optimization (PSO) and Genetic Algorithm...
In this paper, we compare the performance of various gradient based techniques in optimizing the neural networks employed for prediction modeling. Training of neural network based predictive models is done using gradient based techniques, which involves searching for the point of minima on multidimensional energy function by providing step-wise corrective adjustment of weight vector present in hidden...
This paper compares the development of neural network based prediction models for sustainable insurance using gradient techniques for training of the network. Convergence of different gradient algorithms is compared on data sets taken from life insurance in the rural sector. For applying these gradient based algorithms, prediction models based on neural networks are simulated in MATLAB Neural Network...
A country's growth is strongly measured by quality of its education system. Education sector, across the globe has witnessed sea change in its functioning. Today it is recognized as an industry and like any other industry it is facing challenges, the major challenges of higher education being decrease in students' success rate and their leaving a course without completion. An early prediction of students'...
The voluminous amount of data stored in databases contains hidden knowledge which could be valuable to improve decision making process of any organization. As it is not humanely possible to analyze large databases, it has become essential to apply advanced data mining algorithms for extracting patterns (models) from data to support decision making. A number of data mining algorithms produce information...
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