Mastering OpenCV 4 with Python

Supervised machine learning

Supervised learning is performed using a collection of samples with the corresponding output values (desired output) for each sample. These machine learning methods are called supervised because we know the correct answer for each training example and the supervised learning algorithm analyzes the training data in order to make predictions on the training data. Besides, these predictions can be corrected based on the difference between the prediction and the corresponding desired output. Based on these corrections, the algorithm can learn from the mistakes to adjust its internal parameters. This way, in supervised learning, the algorithm iteratively adjusts a function, which best approximates the relationship between ...