The main purpose of forecasting by data mining in the stock market is to discover knowledge that can assist decision-makers. It is important that companies use data mining with utmost care to improve their business by increasing revenue and reducing costs (Ahmed, 2004). For example, Amazon ...
Experiments have been performed using data from the Nokia Mobile Data Challenge (MDC). The results on MDC data show large variability in predictive accuracy of about 17% across users. For example, irregular users are very difficult to predict while for more regular users it is possible to ...
Classification is one of the supervised learning methods in data mining. The main goal of classification is to connect the input variables with the target variables and make predictions based on this relationship. The classification techniques used in this study ranged from decision tree to support ...
Two hyperparameters are needed for the SVM algorithm: cost (C), which indicates the degree of penalty for misclassification, and gamma (γ), which defines the extent of the influence of a single training example. In this study, we adopted the Gaussian radial basis kernel for SVM. The “...
Oracle Data Mining Conceptsfor information about predictive data mining. Note: The following example is excerpted from the Data Mining sample programs. For more information about the sample programs, see Appendix A inOracle Data Mining User's Guide. ...
3.2 Illustrative example Considering the \({\mathrm{NO}}_{2}\) Emissions prediction problem described in Sect. 2.2, the Directive 2008/50/EC contains information on the relevance of certain data points. In particular, the goal to maintain the LNO2 hourly concentration values below a limit equ...
An empirical learning curve often exhibits three primary learning regions: small-data, power law, and irreducible error [20]. Figure 1 provides a glimpse into the experimental results discussed later. All three learning regions of the power law expression in Eq. (1) are distinguishable on the ...
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For example, CVC or PICC insertion and a history of DVT and PE have been extensively investigated as high-risk factors for VTE30,31. In addition, life-threatening illness and fibrinogen have been confirmed by a recent meta-analysis to be related to the risk of VTE, and these factors are ...
An example of the raw time series data of a CT equipment Full size image To further distinguish the arcing generation from other situations, new features are constructed and considered in the model. The new features including Daily Tube Scanning Time (DTST) and Daily Consumption of Electrical En...