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Figure 2 Generalization accuracy.
Bootstrap re-sampling was used to enhance the generalization accuracy of the model, using 20 re-sampling trials.
However, a more comprehensive study on the improvements in generalization accuracy upon optimizing various model parameters would be desirable.
Before starting the pattern search, the generalization accuracy is always assessed with the default model parameter configuration.
Assessing the generalization accuracy of a learner with optimized model hyper-parameters with the double loop data sampling algorithm.
The quantization is typically accompanied by a loss of information that tends to reduce the generalization accuracy.
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Additionally, the patterns in generalization accuracies are complex, and the relationship between pairs of training and testing images is not necessarily reciprocal, i.e., good training data are not necessarily good testing data.
Accuracy exceeding 0.5 on these novel test items indicates rule-based generalization, while accuracy below 0.5 indicates feature-based generalization.
Furthermore, available empirical correlations do not have satisfying generalization and accuracy owing to being calibrated on specific oil samples.
In addition, modified mathematical equation to evaluate consequences of risk which allow more generalization and accuracy of weighing the possible losses (performance, financial, ecology and human) is developed.
The results demonstrate that the SVM-based method provides superior performance in generalization and accuracy and can be a powerful tool for nonlinear system simulation and prediction.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com