Answer: output value
Explanation: Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs.
Supervised learning infers a function from labeled training data consisting of a set of training examples.
In supervised learning, each example consists of a pair of an input object (a vector) and a desired output value (the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples. An optimal scenario will allow for the algorithm to correctly determine the class labels for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way
A wide range of supervised learning algorithms are available, each having its own strengths and weaknesses.
You should now that, there is no single learning algorithm that works better than the other on all supervised learning problems
Answer:
Explanation:
Answer: With crumple zones at the front and back of most cars, they absorb much of the energy (and force) in a crash by folding in on itself much like an accordion. ... As Newton's second law explains force = Mass x Acceleration this delay reduces the force that drivers and passengers feel in a crash.Sep 30, 2020
A design is a plan or specification for the construction of an object or system or for the implementation of an activity or process, or the result of that plan or specification in the form of a prototype, product or process. The verb to design expresses the process of developing a design.
