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This paper focuses on different feature selection techniques applied on the huge number of datasets of an airline databases to understand and clean the dataset. CFS Subset Evaluator, Consistency Subset Evaluator, Gain Ratio feature evaluator, Information Gain Attribute Evaluator, OneR feature evaluator, Principal Components Attribute Transformer (PCA), ReliefF Attribute Evaluator and Symmetrical Uncertainty...
This paper focuses an overview of the main clustering techniques and classification algorithms for evaluation of risk and safety in civil aviation industry. This paper aim to study the performance of different clustering algorithms is correlated based on the time taken to build model arrangement the evaluated clusters. The Database contains number of accident data records for all categories of aviation...
Data mining approaches have been successfully applied in different fields. Risk and safety have always been important considerations in aviation. There is a large amount of knowledge and data accumulation in aviation industry. These data can be store in the form of pilot reports, maintenance reports, accident reports or delay reports. This paper applied the decision tree model on accident reports...
In machine learning, selection of optimal features for the classifier is a critical problem. In order to address this problem a novel feature selection method named “Improved Normalized Point wise Mutual Information (INPMI)” is proposed. The proposed INPMI method coupled with Sequential forward search (SFS) finds the best feature subset to aid feature selection process. The key properties of evaluating...
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