Load LightGBM takes in either a file path or model string. If both are provided, Load will default to loading from file
lgb.load(filename = NULL, model_str = NULL)
filename | path of model file |
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model_str | a str containing the model (as a |
lgb.Booster
# \donttest{ data(agaricus.train, package = "lightgbm") train <- agaricus.train dtrain <- lgb.Dataset(train$data, label = train$label) data(agaricus.test, package = "lightgbm") test <- agaricus.test dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) params <- list( objective = "regression" , metric = "l2" , min_data = 1L , learning_rate = 1.0 ) valids <- list(test = dtest) model <- lgb.train( params = params , data = dtrain , nrounds = 5L , valids = valids , early_stopping_rounds = 3L ) #> [LightGBM] [Warning] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000974 seconds. #> You can set `force_row_wise=true` to remove the overhead. #> And if memory is not enough, you can set `force_col_wise=true`. #> [LightGBM] [Info] Total Bins 232 #> [LightGBM] [Info] Number of data points in the train set: 6513, number of used features: 116 #> [LightGBM] [Info] Start training from score 0.482113 #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [1] "[1]: test's l2:6.44165e-17" #> [1] "Will train until there is no improvement in 3 rounds." #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [1] "[2]: test's l2:1.97215e-31" #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [1] "[3]: test's l2:0" #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [LightGBM] [Warning] Stopped training because there are no more leaves that meet the split requirements #> [1] "[4]: test's l2:0" #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [LightGBM] [Warning] Stopped training because there are no more leaves that meet the split requirements #> [1] "[5]: test's l2:0" #> [1] "Did not meet early stopping, best iteration is: [3]: test's l2:0" model_file <- tempfile(fileext = ".txt") lgb.save(model, model_file) load_booster <- lgb.load(filename = model_file) model_string <- model$save_model_to_string(NULL) # saves best iteration load_booster_from_str <- lgb.load(model_str = model_string) # }