Closed Soledad89 closed 7 years ago
How do you train this model? python/R or cli? can you paste the full model file?
@guolinke I just run the multiclass_class example with my own datasets, that has 18 classes and 50-dimention feature vector
# task type, support train and predict
task = train
# boosting type, support gbdt for now, alias: boosting, boost
boosting_type = gbdt
# application type, support following application
# regression , regression task
# binary , binary classification task
# lambdarank , lambdarank task
# multiclass
# alias: application, app
objective = multiclass
# eval metrics, support multi metric, delimite by ',' , support following metrics
# l1
# l2 , default metric for regression
# ndcg , default metric for lambdarank
# auc
# binary_logloss , default metric for binary
# binary_error
# multi_logloss
# multi_error
metric = multi_logloss
# number of class, for multiclass classification
num_class = 18
# frequence for metric output
metric_freq = 1
# true if need output metric for training data, alias: tranining_metric, train_metric
is_training_metric = true
# number of bins for feature bucket, 255 is a recommend setting, it can save memories, and also has good accuracy.
max_bin = 255
# training data
# if exsting weight file, should name to "regression.train.weight"
# alias: train_data, train
data = multiclass.train
# valid data
valid_data = multiclass.test
# round for early stopping
early_stopping = 32
# number of trees(iterations), alias: num_tree, num_iteration, num_iterations, num_round, num_rounds
num_trees = 6400
# shrinkage rate , alias: shrinkage_rate
learning_rate = 0.05
# number of leaves for one tree, alias: num_leaf
num_leaves = 128
@Soledad89 , could you also share your training samples snippet?
@chivee Of course yes.
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@Soledad89 I mean the LightGBM_model.txt
file.
@Soledad89 BTW, it seems you didn't use the latest code. Can you try the latest code(master branch) ?
@guolinke @chivee Great. While, I have tried the latest code and solved the issue. I suppose that it's my fault. The label should start from zero. That's the bad boy. Thanks soooo much for your kind reply.
This issue has been automatically locked since there has not been any recent activity since it was closed. To start a new related discussion, open a new issue at https://github.com/microsoft/LightGBM/issues including a reference to this.
Has anybody encountered this error: Met Exceptions: Tree model string format error
I found that the model (LightGBM_model.txt) I have trained contains some codes as below:
num_leaves=1 split_feature= split_gain= threshold= decision_type= left_child= right_child= leaf_parent=-1 leaf_value=0 leaf_count=0 internal_value= internal_count= shrinkage=1
That's the bad boy. How to solve this kind of problem during training process? Thanks so much.