Exact(2)
Additionally, the results of different studies are difficult to compare due to different empirical setups and data preprocessing, possibly leading to contradictory results.
In addition, the results of different studies are difficult to compare due to their different empirical setups, data preprocessing, and dataset characteristics (Shepperd and MacDonell 2012; Langdon et al. 2016).
Similar(58)
Either such procedure can be sensible in different empirical contexts.
In regards to the prediction accuracy, our approach allows to compare results across different models applying the same empirical setup and data preprocessing.
In the training as well as in the test period, the empirical setup is structured as follows.
Our study compares all performance metrics results across the same empirical setup, data preprocessing and attribute selectors.
It is defined in Eq. 2. Our study compares results across the same empirical setup, data preprocessing and attribute selectors.
The advantage of our empirical setup is the clear time-line and its simplicity.
As already mentioned above, experiments probing different setups and different kinetic regimes are sensitive to different parameters.
We discuss two different circuit setups.
Two different experimental setups were used to acquire the data for this study.
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