Function for making predictions from trained ExtraTree object.
This function makes predictions for regression/classification using the given trained ExtraTree object and provided input matrix (newdata).
## S3 method for class 'extraTrees' predict(object, newdata, quantile=NULL, allValues=F, probability=F, newtasks=NULL, ...)
object |
extraTree (S3) object, created by extraTrees(). |
newdata |
a new numberic input data matrix, for each row a prediction is made. |
quantile |
the quantile value between 0.0 and 1.0 for quantile regression, or NULL (default) for standard predictions. |
allValues |
whether or not to return outputs of all trees (default FALSE). |
probability |
whether to return a matrix of class (factor) probabilities, default FALSE. Can only be used in the case of classification. Calculated as the proportion of trees voting for particular class. |
newtasks |
list of tasks, for each input in newdata (default NULL). Must be NULL if no multi-task learning was used at training. |
... |
not used currently. |
The vector of predictions from the ExtraTree et. The length of the vector is equal to the the number of rows in newdata.
Jaak Simm
## Regression with ExtraTrees: n <- 1000 ## number of samples p <- 5 ## number of dimensions x <- matrix(runif(n*p), n, p) y <- (x[,1]>0.5) + 0.8*(x[,2]>0.6) + 0.5*(x[,3]>0.4) + 0.1*runif(nrow(x)) et <- extraTrees(x, y, nodesize=3, mtry=p, numRandomCuts=2) yhat <- predict(et, x)
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