Figure 6 | Scientific Reports

Figure 6

From: Novel AI driven approach to classify infant motor functions

Figure 6

Results of hyperparameter tuning obtained with SMNN 5. (a) Batch size \(N_{batch}\), (b) number of frames per input vector \(N_{stack}\), and (c) offset between two consecutive input vectors \(N_{slide}\). Left: TPR vs. FPR scores for hyperparameter tuning (the value closest to the TPR = 1 and FPR = 0 corresponds to the best perfromance). Middle: distance \(d = \sqrt{\left( 1-\mathrm {TPR}\right) ^2 + \left( \mathrm {FPR}\right) ^2}\) with respect to TPR = 1 and FPR = 0 (the lowest value corresponds to the best performance). Right: classification accuracy (the highest value corresponds to the best performance). Red dot denotes the parameter with the best performance.

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