File size: 3,276 Bytes
328a1a9 |
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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
search_space = ps(
booster = p_fct(levels = c("gblinear", "gbtree", "dart")),
nrounds = p_dbl(lower = 1, upper = log(2000), tags = c("int", "log"), trafo = function(x) as.integer(round(exp(x)))),
eta = p_dbl(lower = log(1e-4), upper = log(1), tags = "log", trafo = function(x) exp(x), depends = booster %in% c("dart", "gbtree")),
gamma = p_dbl(lower = log(1e-4), upper = log(7), tags = "log", trafo = function(x) exp(x), depends = booster %in% c("dart", "gbtree")),
lambda = p_dbl(lower = log(1e-4), upper = log(1000), tags = "log", trafo = function(x) exp(x)),
alpha = p_dbl(lower = log(1e-4), upper = log(1000), tags = "log", trafo = function(x) exp(x)),
subsample = p_dbl(lower = 0.1, upper = 1),
max_depth = p_int(lower = 1L, upper = 15L, depends = booster %in% c("dart", "gbtree")),
min_child_weight = p_dbl(lower = 1, upper = log(150), tags = "log", trafo = function(x) exp(x), depends = booster %in% c("dart", "gbtree")),
colsample_bytree = p_dbl(lower = 0.01, upper = 1, depends = booster %in% c("dart", "gbtree")),
colsample_bylevel = p_dbl(lower = 0.01, upper = 1, depends = booster %in% c("dart", "gbtree")),
rate_drop = p_dbl(lower = 0, upper = 1, depends = booster == "dart"),
skip_drop = p_dbl(lower = 0, upper = 1, depends = booster == "dart"),
trainsize = p_dbl(lower = 0.03, upper = 1, tags = "budget"),
task_id = p_fct(levels = c("40981", "41146", "1489", "1067"), tags = "task_id")
)
domain = ps(
booster = p_fct(levels = c("gblinear", "gbtree", "dart")),
nrounds = p_int(lower = 3, upper = 2000),
eta = p_dbl(lower = 1e-4, upper = 1, depends = booster %in% c("dart", "gbtree")),
gamma = p_dbl(lower = 1e-4, upper = 7, depends = booster %in% c("dart", "gbtree")),
lambda = p_dbl(lower = 1e-4, upper = 1000),
alpha = p_dbl(lower = 1e-4, upper = 1000),
subsample = p_dbl(lower = 0.1, upper = 1),
max_depth = p_int(lower = 1L, upper = 15L, depends = booster %in% c("dart", "gbtree")),
min_child_weight = p_dbl(lower = exp(1), upper = 150, depends = booster %in% c("dart", "gbtree")),
colsample_bytree = p_dbl(lower = 0.01, upper = 1, depends = booster %in% c("dart", "gbtree")),
colsample_bylevel = p_dbl(lower = 0.01, upper = 1, depends = booster %in% c("dart", "gbtree")),
rate_drop = p_dbl(lower = 0, upper = 1, depends = booster == "dart"),
skip_drop = p_dbl(lower = 0, upper = 1, depends = booster == "dart"),
trainsize = p_dbl(lower = 0.03, upper = 1, tags = "budget"),
task_id = p_fct(levels = c("40981", "41146", "1489", "1067"), tags = "task_id")
)
codomain = ps(
mmce = p_dbl(lower = 0, upper = 1, tags = "minimize"),
f1 = p_dbl(lower = 0, upper = 1, tags = "maximize"),
auc = p_dbl(lower = 0, upper = 1, tags = "maximize"),
logloss = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
ramtrain = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
rammodel = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
rampredict = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
timetrain = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
timepredict = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
mec = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
ias = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
nf = p_dbl(lower = 0, upper = Inf, tags = "minimize")
)
|