How to store and analyze classification results with Python? I'm applying ML for classification task in Python using sklearn/pandas. I'm going to try various things to get the best results, and I wonder how do I effectively store and analyze all the parameters and results of the classification? Parameters include:


Number of training examples (which can be extended as I get more labeled data).
Set of features.
Classification algorithm.
Algorithm hyperparameters.


Results include:


Precision/recall for each of the classes.
Overall precision/recall.
Support for each class, etc.


Of course, I can manually copy the parameters and results to an Excel spreadsheet every time, but it's not an optimal solution. Are there any Python libraries (or modules of sklearn/pandas) which allow to easily store and display the parameters and results for later analysis? How do you solve this task?
Sacred is a python library developed by the IDSIA lab that "facilitates automated and reproducible experimental research". It is available through pip as sacred.

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