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Intensive Care Unit (ICU) admission is a major factor that affects the healthcare budget. ICU cost is extremely high because its resources are consumed through highly advanced equipment providing quality healthcare service for patients. Thus, the need for a predictive model for the decision to transfer stroke in-patients to the ICU is very important. Also, this predictive model will help to lower...
In these days, chronic diseases are the imperative reason for death in the world. Therefore, there is a noteworthy increment in consideration being paid to individual wellness as a preventative methodology in healthcare. However, creating and building a prediction model for chronic diseases is an extraordinary change to healthcare technology on the premise of data-analysis and decision-making level...
One of the key success factors of lending organizations in general and banks in particular is the assessment of borrower credit worthiness in advance during the credit evaluation process. Credit scoring models have been applied by many researchers to improve the process of assessing credit worthiness by differentiating between prospective loans on the basis of the likelihood of repayment. Thus, credit...
Individual credit risk evaluation is an important and challenging data mining problem in financial analysis domain. This paper compares the effectiveness of four data mining algorithms - logistic regression (LR), decision tree (C4.5), support vector machine (SVM) and neural networks (NN) by applying them to two credit data sets. Experiment results show that the LR and SVM algorithms produced the best...
City scientific and technological progress level classification and promotion play a central role in spurring city income growth and reducing poverty. Based on the Chinese city data availability, this paper built evaluation index system on the level of city scientific and technological progress. According to the city scientific and technological progress data which is large scale and imbalance, this...
Innovation system efficiency analysis and prediction play an important role in regional innovation systems development and improve benefit of innovative capacity for country. According to the county innovation system data which is large scale and imbalance, this paper presented a support vector machine model to predict county innovation system efficiency. The method was compared with artificial neural...
Rough set theory (RST), support vector machine (SVM), and decision tree (DT) are brightly data mining methodologies for classification prediction tasks. While the accuracy for class prediction is highly emphasized, the ability to generate rules for decision support is also important in some practical applications. Studies have shown the ability of RST for feature selection while SVM and DT are significantly...
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