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L'accuratezza della macchina con incremento gradiente diminuisce all'aumentare del numero di iterazioni
Sto sperimentando l'algoritmo della macchina per aumentare il gradiente tramite il caretpacchetto in R. Utilizzando un piccolo set di dati di ammissione al college, ho eseguito il seguente codice: 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] <- …
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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
references
terminology
cross-correlation
definition
probability
distributions
beta-distribution
inverse-gamma
missing-data
paired-comparisons
paired-data
clustered-standard-errors
cluster-sample
time-series
arima
logistic
binary-data
odds-ratio
medicine
hypothesis-testing
wilcoxon-mann-whitney
unsupervised-learning
hierarchical-clustering
neural-networks
train
clustering
k-means
regression
ordinal-data
change-scores
machine-learning
experiment-design
roc
precision-recall
auc
stata
multilevel-analysis
regression
fitting
nonlinear
jmp
r
data-visualization
gam
gamm4
r
lme4-nlme
many-categories
regression
causality
instrumental-variables
endogeneity
controlling-for-a-variable