Access Training Metrics

[chris-smith-zocdoc]

Is your feature request related to a problem? Please describe. I'd like to be able to access the metrics produced during model training. Currently I only see metrics in the logs and need to run my own prediction + evaluation after model training, which seems wasteful.

Describe the solution you'd like

ranker = LightGBMRanker()
model = ranker.fit(df)

# access summary statistics about the training 
metric_history = model.summary.metrics['training']['ndcg@5']
print(metric_history) -> [.001, .01, .7]

Additional context Having a summary field on the model returned by training is something other spark libraries have done. XGBoost, MLLib

[svenharris]

Has any work been done on this? Would also find the feature very useful, happy to contribute if it's within my skill level (which I suspect it may not be)