R error : Unknown parameter: nrounds

[klyan]

Error Message:

dtrain <- lgb.Dataset(as.matrix(train.data), label = train.label)
dtest <- lgb.Dataset(as.matrix(test.data), label = test.label)
params <- list(objective = "lambdarank", metric = "ndcg", ndcg_eval_at = 1,3,5,7,10, max_depth = 3, verbose = 1, num_threads = 10)
model <- lgb.train(params, data = dtrain, nrounds = 300, learning_rate = 0.1, early_stopping_rounds = 10, weight=train.weight, group = train.group)

[LightGBM] [Fatal] Unknown parameter: nrounds
Error in lgb.call("LGBM_DatasetCreateFromMat_R", ret = handle, private$raw_data, :
api error: Unknown parameter: nrounds

Are there any errors in my parameter config??

[klyan]

I repace "nrounds" with "num_trees" or "num_iterations", even remove nrounds parameter, it doesn't work.
How could I control the iterations for lambdarank?

model <- lgb.train(params, data = dtrain, num_iterations = 300, learning_rate = 0.1, early_stopping_rounds = 10, weight=train.weight, group = train.group)
[LightGBM] [Fatal] Unknown parameter: nrounds
Error in lgb.call("LGBM_DatasetCreateFromMat_R", ret = handle, private$raw_data, :
api error: Unknown parameter: nrounds
model <- lgb.train(params, data = dtrain, learning_rate = 0.1, early_stopping_rounds = 10, weight=train.weight, group = train.group)
[LightGBM] [Fatal] Unknown parameter: nrounds
Error in lgb.call("LGBM_DatasetCreateFromMat_R", ret = handle, private$raw_data, :
api error: Unknown parameter: nrounds

[guolinke]

@klyan nrounds should work, I just test it.
Maybe you need to restart R.
And you also can try model <- lgb.train(params, dtrain, 300, learning_rate = 0.1, early_stopping_rounds = 10, weight=train.weight, group = train.group)

[klyan]

I restarted R, But it still doesn't work for me.

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library("xgboost")
library("rjson")
library("stringi")
library("caTools")
library("lightgbm")
Loading required package: R6

Attaching package: ‘lightgbm’

The following objects are masked from ‘package:xgboost’:

getinfo, setinfo, slice

load("ligbm.RData")
params <- list(objective = "lambdarank", metric = "ndcg", ndcg_eval_at = 1,3,5,7,10, max_depth = 3, verbose = 1, num_threads = 10)
model <- lgb.train(params, data = dtrain, nrounds = 300, learning_rate = 0.1, early_stopping_rounds = 10, weight=train.weight, group = train.group)
[LightGBM] [Fatal] Unknown parameter: nrounds
Error in lgb.call("LGBM_DatasetCreateFromMat_R", ret = handle, private$raw_data, :
api error: Unknown parameter: nrounds

[guolinke]

@Laurae2 any ideas ? it seems the nrounds parameter is not captured correctly. Maybe the reason is the version of R is too old.

@klyan another problem is you cannot use early_stopping_rounds if you don't pass the validation data in lgb.train .

[guolinke]

@klyan and the weight and group is the parameter of lgb.Dataset, not the lgb.train.

[Laurae2]

@guolinke Seems the parameters passed in params are not correct (like ndcg_eval_at)

[Laurae2]

@klyan Can you provide a reproducible example so we can test?

[klyan]

@Laurae2 @guolinke
The fowllowing script is my code. The training data have 3 labels: 0 for view, 0.6 for click but not ordered, 1 for ordered. Then I set the training weight 30 for ordered sample.
I have fixed the ndcg_eval_at, weight and group parameters in my code. Still doesn't work.
Thanks you very much!

library("lightgbm")

csvdata <- read.csv("/data/pairwise/train1.csv",sep='\t')
csvdata1 <- read.csv("/data/pairwise/test.csv",sep='\t')

#selected features for training
removecol <- c("modelscore","dpid","shop_id","label","real_order","groupcnt")
train.data <- csvdata[,which(!colnames(csvdata) %in% removecol)]
test.data <- csvdata1[,which(!colnames(csvdata1) %in% removecol)]

#set 3 label; view：0 click_notorder：0.6 order：1
csvdata[csvdata[,"real_order"] == 0 & csvdata[,"label"] == 1,"real_order"] <- 0.6
csvdata1[csvdata1[,"real_order"] == 0 & csvdata1[,"label"] == 1,"real_order"] <- 0.6
train.label <- csvdata$real_order
test.label <- csvdata1$real_order

#set group by userid(query)
train.group <- unique(csvdata[,c("dpid","groupcnt")])
test.group <- unique(csvdata1[,c("dpid","groupcnt")])
train.group <- train.group[,"groupcnt"]
test.group <- test.group[,"groupcnt"]

#set sample weight
train.weight <- rep(1,nrow(csvdata))
train.weight[csvdata$real_order == 1] <- 30
test.weight <- rep(1,nrow(csvdata1))
test.weight[csvdata1$real_order == 1] <- 30

dtrain <- lgb.Dataset(as.matrix(train.data), label = train.label, weight=train.weight, group = train.group)
dtest <- lgb.Dataset(as.matrix(test.data), label = test.label)

params <- list(objective = "lambdarank", metric = "ndcg", max_depth = 3, verbose = 1, num_threads = 10)
model <- lgb.train(params, data = dtrain, nrounds = 300, learning_rate = 0.1)

[guolinke]

@klyan we cannot reproduce it since we don't have your data. you can use agaricus data:

data(agaricus.train, package = "lightgbm")
data(agaricus.test, package = "lightgbm")
train <- agaricus.train
test <- agaricus.test

Also, you can format your code for the better readability .

I also try some other cases, but still not met your problem.

[guolinke]

@klyan updates ?

[zheguzai100]

try nround=300

[klyan]

@guolinke Sorry, it's too big to upload my data. And I try my data in latest R version in MacOS, get the same error. But python package is OK for me.(I have updated my code, above) . Thanks a lot!
@zheguzai100 'nround' doesn't work

[guolinke]

@klyan can you try it without using group, and change objective to regression ?

[klyan]

@guolinke
Yes! it works!

lgb.unloader(wipe = TRUE)

makes both of them work.
It seems that somes errors in my environment. And I save variable into RData, then restart my R. But doesn't fix it and 'lgb.unloader(wipe = TRUE)' fix it