cv.mada {bst} | R Documentation |
Cross-validated estimation of the empirical misclassification error for boosting parameter selection.
cv.mada(x, y, balance=FALSE, K=10, nu=0.1, mstop=200, interaction.depth=1, trace=FALSE, plot.it = TRUE, se = TRUE, ...)
x |
a data matrix containing the variables in the model. |
y |
vector of multi class responses. |
balance |
logical value. If TRUE, The K parts were roughly balanced, ensuring that the classes were distributed proportionally among each of the K parts. |
K |
K-fold cross-validation |
nu |
a small number (between 0 and 1) defining the step size or shrinkage parameter. |
mstop |
number of boosting iteration. |
interaction.depth |
used in gbm to specify the depth of trees. |
trace |
if TRUE, iteration results printed out. |
plot.it |
a logical value, to plot the cross-validation error if |
se |
a logical value, to plot with 1 standard deviation curves. |
... |
additional arguments. |
object with
residmat |
empirical risks in each cross-validation at boosting iterations |
fraction |
abscissa values at which CV curve should be computed. |
cv |
The CV curve at each value of fraction |
cv.error |
The standard error of the CV curve |
...