Mastering Machine Learning for Penetration Testing

Selecting models and learning curves

To improve the performance of machine learning models, there are many hyper parameters to adjust. The more data that is used, the more errors that can happen. To work on these parameters, there is a method called GridSearchCV. It performs searches on predefined parameter values, through iterations. GridSearchCV uses the score() function, by default. To use it in scikit-learn, import it by using this line:

from sklearn.grid_search import GridSearchCV

Learning curves are used to understand the performance of a machine learning model. To use a learning curve in scikit-learn, import it to your Python project, as follows:

from sklearn.learning_curve import learning_curve