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In the case of a synthetic data set the agreement of analytical and numerical results is satisfactory.
The synthetic data set successfully incorporates much of the covariance structure of the underlying field data and supports multivariate modeling.
Extensive experiments have been conducted on the synthetic data set to verify the feasibility of our protocol.
Finally, we deliver the proof of concept for the inversion using a synthetic data set with a noise level of up to 5%.
This paper evaluates the system using a real-world data set and a large synthetic data set, and compares with three baselines.
We also present results from an experiment using the stagger Concepts, a synthetic data set involving concept drift, suggesting that our methods perform comparably to the flora2 system in terms of predictive accuracy, but store fewer examples.
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Using semi-synthetic data set, we evaluated the robustness of SiS simulating many different experimental conditions.
The semi-synthetic data set presented here represents a suitable instrument for testing the efficacy of new statistics for exon-level analysis.
Semi-synthetic data set We downloaded five different signaling networks (VEGF, Apoptosis, WNT, ERB and MAPK) of human (Homo sapiens) from KEGG database.
In our semi-synthetic data set the new genes, characterized by skipping events, are generated using different associations of spike-in concentrations to evaluate the effect of signal intensity in the detection of alternative splicing.
We demonstrated experimentally that SiS is robust by simulating a broad spectrum of parameters determining the network topologies and result characteristics by testing it on the semi-synthetic data set.
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