A secure biometrics system authenticates the user based on his/her physiological (e. g., fingerprint, face, voice) or behavioral (e. g., gait, hand gesture, keystroke) traits. Typically, a binary classification model will be developed to generate predicted probabilities based on the input information. Please explain:

The solution to this question can be defined as follows:

Explanation:

please find the complete question in the attached file:

In point a:

It utilizes multiple algorithms based on machine learning can understand the attributes or transform their probability into projections. Its algorithms could be used, including such neural computer systems or artificial neural networks. Whenever the input, as well as the target outcome, are taken their possibilities are converted in forecasts, so that if the input, as well as the corresponding results, are balanced.

In point b:

The operating curves of its receiver is indeed a plot of its true positives for its incorrect positive rate. It could be used in different tests for treatment. It indicates the variations of its responsiveness between all the two components and also the accuracy. Line slopes supply LR with a value.

are there any graphs invested in this equation