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 ...
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 ...
Fig. 1. TOB optimized data matching methodology configured for predicting and data mining highly skewed carbon-flux (net ecosystem carbon exchange; NEE) datasets. TOB Stage 1 assesses data-record matches between records in small, evenly distributed subset designed to tune the algorithm with a larger...
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. ...
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 ...
In some cases, it can be important to approximate the range of a target measure of interest instead of computing exact values. For example, selling a stock at a given time can be based on a range containing the target price rather than the exact amount because of the transaction cost. ...
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...
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 “...
For example, reliability is one of the significant aspects that widely considered by most researchers nowadays. Basically, the error evaluation criteria are supposed to be easily adapted in real situations and should be selected according to the actual needs of the method design. Computation time is...