Planning the app

The final app will parse a dataset, train the ensemble classifier, assess its classification performance, and visualize the result. This will require the following components:

• main: The main function routine (in chapter6.py) for starting the application.
• datasets.gtsrb: A script for parsing the German Traffic Sign Recognition Benchmark (GTSRB) dataset. This script contains the following functions:
  • load_data: A function used to load the GTSRB dataset, extract a feature of choice, and split the data into training and test sets.
  • _extract_features: A function that is called by load_data to extract a feature of choice from the dataset.
• classifiers.Classifier: An abstract base class that defines the common interface for all classifiers.
• classifiers.MultiClassSVM: A class that implements an ensemble of SVMs for multiclass classification using the following public methods:
  • MultiClassSVM.fit: A method used to fit the ensemble of SVMs to training data. It takes a matrix of training data...