Skip to main content

Table 4 Optimized parameters of RF, GBR, and SVR

From: Using improved support vector regression to predict the transmitted energy consumption data by distributed wireless sensor network

MethodsParametersParameter descriptionTerminal values
RFn_estimatorsThe number of trees in the forest10
 max_depthThe depth of a tree7
GBRmax_depthThe depth of a tree7
 learning_rateThe learning rate0.19
 n_estimatorsThe number of trees40
SVCThe penalty parameter150
 εInsensitive loss coefficient0.08
 γγ defines how much influence a single training example has. The larger the γ is, the closer other example must be to be affected.0.1