Research Article
Round Randomized Learning Vector Quantization for Brain Tumor Imaging
Algorithm 2
Classification based on multiresampling method.
Input: Preprocessed data set using (PCA) filter. | Output: The best accuracy rate | For to 50 | Random the dataset by swapping each instance with next | Select the evaluation method | If cross validation then input fold number | else | select split percentage | input the required splitting percentage | Build the model using the training data set | Evaluate the model using testing data | If the new accuracy rate > current best accuracy rate Then | Best accuracy rate = new accuracy rate | Else | new accuracy rate = current best accuracy rate | Next I | Print out the best accuracy rate | End. |
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