We obtained a dataset Animal to develop two models: Model$1$ and Model$2,$ which are used to predict the value of Type. We have loaded the data to object Animal into software and compared the performance of the two models. Model outputs are shown as below. Based on the outputs, which of the statements is$($are$)$ true? $>$ dim$($Animal$)[1]1000016>$ contrasts$($Type$)$ ReptileAmphibian $0$Reptile $1>$ trainTree $=$ sample$(1$:nrow$($Animal$),$ nrow$($Animal$)*0\mathrm{.}7)>$ Animal.train $=$ Animal$[$trainTree$,]>$ Animal.test $=$ Animal$[-$trainTree, $]>$ train.truevalue$=$Type$[$trainTree$]>$ test.truevalue$=$Type$[-$trainTree$]>$ Model$1=$randomForest$($Type ~ $.,$ data $=$ Animal.train, mtry$=4,$importance$=$TRUE$)>$ Model$1.$pred.train $=$ predict$($Model$1,$Animal.train$)>$ mean$($Model$1.$pred.train$==$train.truevalue$)[1]0\mathrm{.}90>$ Model$1.$pred.test$=$ predict$($Model$1,$Animal.test$)>$ mean$($Model$1.$pred.test$==$test.truevalue$)[1]0\mathrm{.}83>$ Model$2=$randomForest$($Type ~ $.,$ data $=$ Animal.train, mtry$=15,$importance$=$TRUE$)>$ Model$2.$pred.train $=$ predict$($Model$2,$Animal.train$)>$ mean$($Model$2.$pred.train$==$train.truevalue$)[1]0\mathrm{.}98>$ Model$2.$pred.test$=$ predict$($Model$2,$Animal.test$)>$ mean$($Model$2.$pred.test$==$test.truevalue$)[1]0\mathrm{.}81$