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梯度提升机的精度随着迭代次数的增加而降低
我正在通过caretR中的程序包尝试使用梯度增强机算法。 使用一个小的大学录取数据集,我运行了以下代码: library(caret) ### Load admissions dataset. ### mydata <- read.csv("http://www.ats.ucla.edu/stat/data/binary.csv") ### Create yes/no levels for admission. ### mydata$admit_factor[mydata$admit==0] <- "no" mydata$admit_factor[mydata$admit==1] <- "yes" ### Gradient boosting machine algorithm. ### set.seed(123) fitControl <- trainControl(method = 'cv', number = 5, summaryFunction=defaultSummary) grid <- expand.grid(n.trees = seq(5000,1000000,5000), interaction.depth = 2, shrinkage = …
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machine-learning
caret
boosting
gbm
hypothesis-testing
t-test
panel-data
psychometrics
intraclass-correlation
generalized-linear-model
categorical-data
binomial
model
intercept
causality
cross-correlation
distributions
ranks
p-value
z-test
sign-test
time-series
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beta-distribution
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missing-data
paired-comparisons
paired-data
clustered-standard-errors
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arima
logistic
binary-data
odds-ratio
medicine
hypothesis-testing
wilcoxon-mann-whitney
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r
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gam
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r
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endogeneity
controlling-for-a-variable