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Table 2 Set of parameters and corresponding ranges tested for each classifier within the grid search scheme

From: Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

Classifier Parameters and respective range
NB Gaussian or Supervised Discrimination or Kernel
DT Confidence [0.05,0.5]
SVM RBF Complexity [10−1, 101] and γ [10−2, 102]
SVM Poly Complexity [10−1, 101] and Degree {1, 2, 3}
kNN #Neighbors [1, 11]
RF #Iterations [5, 30]
LR Ridge [10−9, 10−6]
  1. Note: DT: Decision Tree classifier, kNN: k-nearest neighbor classifier, SVM Poly: polynomial-kernel Support Vector Machines, SVM RB: Gaussian-kernel Support Vector Machines, NB: Naïve Bayes classifier, LR: Logistic Regression and RF: Random Forest