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| author | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2018-04-05 15:53:02 -0400 |
|---|---|---|
| committer | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2018-04-05 15:53:02 -0400 |
| commit | dab6fb67a7a841509c88db51cbbd4724edec1b31 (patch) | |
| tree | a2584c813dd77930b55b298bf616c851e4902a04 | |
| parent | don't run a bunch of examples to make check faster (diff) | |
| download | rgensvm-dab6fb67a7a841509c88db51cbbd4724edec1b31.tar.gz rgensvm-dab6fb67a7a841509c88db51cbbd4724edec1b31.zip | |
making examples faster
| -rw-r--r-- | R/gensvm.R | 11 | ||||
| -rw-r--r-- | man/gensvm.Rd | 15 |
2 files changed, 10 insertions, 16 deletions
@@ -91,14 +91,11 @@ #' x <- iris[, -5] #' y <- iris[, 5] #' -#' # fit using the default parameters -#' fit <- gensvm(x, y) -#' -#' # fit and show progress +#' # fit using the default parameters and show progress #' fit <- gensvm(x, y, verbose=TRUE) #' #' # fit with some changed parameters -#' fit <- gensvm(x, y, lambda=1e-8) +#' fit <- gensvm(x, y, lambda=1e-6) #' #' # Early stopping defined through epsilon #' fit <- gensvm(x, y, epsilon=1e-3) @@ -111,8 +108,8 @@ #' fit <- gensvm(x, y, kernel='poly', degree=2, gamma=1.0, max.iter=1000) #' #' # Setting the random seed and comparing results -#' fit <- gensvm(x, y, random.seed=123) -#' fit2 <- gensvm(x, y, random.seed=123) +#' fit <- gensvm(x, y, random.seed=123, max.iter=1000) +#' fit2 <- gensvm(x, y, random.seed=123, max.iter=1000) #' all.equal(coef(fit), coef(fit2)) #' #' diff --git a/man/gensvm.Rd b/man/gensvm.Rd index cee2b35..18bcd52 100644 --- a/man/gensvm.Rd +++ b/man/gensvm.Rd @@ -99,14 +99,11 @@ the user. x <- iris[, -5] y <- iris[, 5] -# fit using the default parameters -fit <- gensvm(x, y) - -# fit and show progress +# fit using the default parameters and show progress fit <- gensvm(x, y, verbose=TRUE) # fit with some changed parameters -fit <- gensvm(x, y, lambda=1e-8) +fit <- gensvm(x, y, lambda=1e-6) # Early stopping defined through epsilon fit <- gensvm(x, y, epsilon=1e-3) @@ -115,12 +112,12 @@ fit <- gensvm(x, y, epsilon=1e-3) fit <- gensvm(x, y, max.iter=1000) # Nonlinear training -fit <- gensvm(x, y, kernel='rbf', max.iter=5000) -fit <- gensvm(x, y, kernel='poly', degree=2, gamma=1.0, max.iter=5000) +fit <- gensvm(x, y, kernel='rbf', max.iter=1000) +fit <- gensvm(x, y, kernel='poly', degree=2, gamma=1.0, max.iter=1000) # Setting the random seed and comparing results -fit <- gensvm(x, y, random.seed=123) -fit2 <- gensvm(x, y, random.seed=123) +fit <- gensvm(x, y, random.seed=123, max.iter=1000) +fit2 <- gensvm(x, y, random.seed=123, max.iter=1000) all.equal(coef(fit), coef(fit2)) |