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. 2023 Feb 23;13(5):858. doi: 10.3390/diagnostics13050858
Algorithm 1: FHR Classsification using Random Forest
Input: Si⊆{(d1,y1),….,(dn,yn)}
Step1: Perform row and column sampling
Step2: Decision tree DTi for each Si
Step3: PredictionPi ← output of eachSi
Output: P← majority vote of P1,….,Pi