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One of the more prevalent problems when working with bioinformatics datasets is class imbalance, when there are more instances in one class compared to the other class (es). This problem is made worse because frequently, the class of interest is also the minority class. A possible solution is data sampling, a powerful tool for combating class imbalance by adding or removing instances to make the dataset...
In this paper, we study the learning impact of data sampling followed by attribute selection on the classification models built with binary class imbalanced data within the scenario of software quality engineering. We use a wrapper-based attribute ranking technique to select a subset of attributes, and the random undersampling technique (RUS) on the majority class to alleviate the negative effects...
In order to alleviate user fatigue of interactive genetic algorithms with an individual's fuzzy and stochastic fitness, we propose a surrogate model-assisted algorithm by using a directed fuzzy graph to extract user cognition. According to cut-set level and interval dominance probability, we present approaches to construct a directed fuzzy graph of an evolutionary population and calculate an individual's...
In this paper we examine a novel approach to the difficult problem of querying video databases using visual topics with few examples. Typically with visual topics, the examples are not sufficiently diverse to create a robust model of the user's need. As a result, direct modeling using the provided topic examples as training data is inadequate. Otherwise, systems resort to multiple content-based searches...
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