Description Usage Arguments Examples
suggest_gain
Gain and Lift charts are widely used in marketing and related contexts.
They indicate the effectiveness of predictive models compared to the results obtained
without the predictive model.
1 2 | suggest_gain(addTo, outChar, predTag = "pred_test", modelTag = NULL,
cuts = 51, type = NULL)
|
addTo |
Summary list that contains model fits to compare. |
outChar |
A charactor value of output class name. |
predTag |
Select prediction results that contains predTag on their name. |
modelTag |
Select model fits that contains modelTag on their name. |
cuts |
Integer indicating the number of splits of probability buckets. |
type |
Plot different type of charts. "Gain" for gain chart. "Lift" for lift chart. "PctAcc" for accumulated event percent. "Pct" for event percent. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ## Not run:
library(mlbench)
data(PimaIndiansDiabetes)
index <- sample(seq_len(nrow(PimaIndiansDiabetes)), 500)
trainingSet <- PimaIndiansDiabetes[index, ]
testSet <- PimaIndiansDiabetes[-index, ]
x <- trainingSet[, -9]
y <- trainingSet[, 9]
x_test <- testSet[, -9]
y_test <- testSet[, 9]
sSummary <- list()
sSummary <- add_model(sSummary, x, y)
sSummary <- add_model(sSummary, x, y, model = c("C5.0Cost", "glmnet"), modelTag = "others")
sSummary <- add_prob(sSummary, x_test, y_test, outChar = "pos")
suggest_gain(sSummary, outChar = "pos")
suggest_gain(sSummary, outChar = "pos", modelTag = "glm|svm", type = "Lift")
suggest_gain(sSummary, outChar = "pos", modelTag = "glm|svm", type = "PctAcc")
suggest_gain(sSummary, outChar = "pos", modelTag = "glm|svm", type = "Pct")
suggest_gain(sSummary, outChar = "pos", modelTag = "glm|svm", type = "Gain")
suggest_gain(sSummary, outChar = "pos", modelTag = "glm|svm", type = "Gain") + xlim(0, 0.5)
# vignette("modeval") #check a vignette for further details
## End(Not run)
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