Chunk #23 — 2. Materials and Methods — 2.8. Random Forest Classification

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Differentiating Individuals with and without Alcohol Use Disorder Using Resting-State fMRI Functional Connectivity of Reward Network, Neuropsychological Performance, and Impulsivity Measures.

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set at 1000. The optimal number of features analyzed at each node (“Mtry”) in the model was estimated to be 8 (using the “tuneRF” function). The final list of variables that significantly contributed to the classification was tabulated and sorted based on their importance to classification. For the top significant FC variables, the brain connectivity across ROIs was mapped onto a 3-dimensional ICBM atlas [88] using custom Matlab scripts.