aws
csv_weights cannot be set
Reference: 0420645671
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System Information
- Framework (e.g. TensorFlow) / Algorithm (e.g. KMeans): XGBoost
- Framework Version: 0.90
- Python Version: 3
- CPU or GPU:
- Python SDK Version: Latest
- Are you using a custom image:
Describe the problem
Can't establish an XGBoost estimator with csv_weights set to 1, as per https://docs.aws.amazon.com/sagemaker/latest/dg/xgboost.html :
To differentiate the importance of labelled data points use Instance Weight Supports
Amazon SageMaker XGBoost allows customers to differentiate the importance of labelled data points by assigning each instance a weight value. For text/libsvm input, customers can assign weight values to data instances by attaching them after the labels. For example, label:weight idx_0:val_0 idx_1:val_1.... For text/csv input, customers need to turn on the csv_weights flag in the parameters and attach weight values in the column after labels. For example: label,weight,val_0,val_1,...).
Now, the docs don't say where the XGBoost class takes the argument, so I tried the obvious locations which all failed.
Minimal repro / logs
As an estimator paramter:
As a float in the estimator fitting:
As a string in the estimator fitting:
As a fit parameter:
Was this resolved? Is the recommended approach to have this in hyperparameters?
