We need to tune hyperparameters for better a recall. Parameter tuning refers to the better fitting of the parameters in a function such that the performance gets better.

The best parameters set found on development set:

{'C': 0.01}

Grid scores on development set:

 0.916 (+/-0.056) for {'C': 0.01}
 0.907 (+/-0.068) for {'C': 0.1}
 0.916 (+/-0.089) for {'C': 1}
 0.916 (+/-0.089) for {'C': 10}
 0.913 (+/-0.095) for {'C': 100}