Solve using Python

In this problem you are required to pick a benchmark dataset (from UCI repository or other authoritative resources), partition it into train and test components and apply various classification techniques. For each classification technique, you should display in a common plot how the accuracy, precision, recall and f1 score are varying for different ratios of train/test of the original dataset. (Note: there will be a different graph for each classification technique.)