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(3) The robust WELM classifier is used to calculate the classification rates.
We also calculate the classification time of different methods based on the nearest-neighbor classifier with Euclidean distance: FLBP with 0.007079 s per sample, NRLBPs with 0.005682 s per sample, and networks with 0.005043 s per sample.
We can simply calculate the classification accuracy by N1/ l1+ l2 and N2/ l1+ l2.
From the predicted category, we could then calculate the classification accuracy for the ipsi- and contralateral fingers independently.
We used a 218-sample training set that was chosen at random from patients with good and poor prognoses and a 218-sample test set to calculate the classification error.
A binary classification algorithm was nested in PST and was performed to establish the series sub-classifiers and calculate the classification probabilities, such as CLA- i and p(T → A| CLA- i ) as indicated in Figure 7. Prior to each implementation, the genes were selected with the information of the involved training samples and by using the methods described in section 2.3.
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The models were evaluated by calculating the classification errors and the root mean square error of prediction (RMSEP) for independent validation sets.
The choice of k is optimized by calculating the classification algorithm ability with different k values.
After completing the anonymization processes for each dataset, we first calculated the classification error by using RapidMiner Studio.
The performances of the two SVMs are assessed for each combination of these values by calculating the classification accuracy (CA) defined as: Table 1 Values of the used kernel parameters Parameter Values Kernel width parameter, γ 0.1 0.05: 5 Order of polynomial kernel, n 1 0.5: 10 Penalty due to the error, C 1: 1000 C A% = frac{Correctly classified patterns}{Totalkern0.5em patterns}times 100 (100.
To ensure that our classification results were not based on factors randomly discriminating between groups, we reran the whole-brain and ROI-based classification for comparison 30 times by randomly assigning all subjects to the three groups independently from the clinical diagnosis and calculating the classification accuracy by using the leave-one-out procedure described above.
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