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54 lines
1.8 KiB
R
54 lines
1.8 KiB
R
# VT.FOREST.DOUBLE --------------------------------------------------------
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# IF RUNNING DOUBLE FOREST COMPUTATION
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#' A reference class to compute twins via double random forests
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#'
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#' @include forest.R
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#'
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#' @field model_trt1 a caret/RandomForest/randomForest object for treatment T = 1
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#' @field model_trt0 a caret/RandomForest/randomForest object for treatment T = 0
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#'
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#' @import methods
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VT.forest.double <- setRefClass(
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Class = "VT.forest.double",
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contains = "VT.forest",
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fields = list(
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model_trt1 = "ANY",
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model_trt0 = "ANY"
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),
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methods = list(
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initialize = function(vt.object, model_trt1, model_trt0, ...){
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.self$checkModel(model_trt1)
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.self$checkModel(model_trt0)
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.self$model_trt1 <- model_trt1
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.self$model_trt0 <- model_trt0
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callSuper(vt.object, ...)
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},
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computeTwin1 = function(){
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"Compute twin1 with OOB predictions from double forests"
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# Model with treatment (1)
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.self$twin1[.self$vt.object$data[, 2] == 1] <- VT.predict(rfor = .self$model_trt1, type = .self$vt.object$type)
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# Model without treatment (0)
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.self$twin1[vt.object$data[, 2] == 0] <- VT.predict(rfor = .self$model_trt0, type = .self$vt.object$type)
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return(.self$twin1)
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return(invisible(.self$twin1))
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},
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computeTwin2 = function(){
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"Compute twin2 by the other part of data in the other forest"
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# Model with treatment (1)
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.self$twin2[.self$vt.object$data[, 2] == 1] <- VT.predict(.self$model_trt0, newdata = .self$vt.object$getX(1, interactions = F), type = .self$vt.object$type)
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# Model without treatment (0)
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.self$twin2[.self$vt.object$data[, 2] == 0] <- VT.predict(.self$model_trt1, newdata = .self$vt.object$getX(0, interactions = F), type = .self$vt.object$type)
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return(invisible(.self$twin2))
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}
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)
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) |