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:
11.6 mm
Explanation:
With a factor of safety of 5 and a yield strength of 900 MPa the admissible stress is:
σadm = strength / fos
σadm = 900 / 5 = 180 MPa
The stress is the load divided by the section:
σ = P / A
σ = 4*P / (π*d^2)
Rearranging:
d^2 = 4*P / (π*σ)


Answer:
newspaper, radio, televison
Explanation:
had avid in 7th :)
Answer:
b. A view of a building seen from one side, a flat representation of one façade. This is the most common view used to describe the external appearance of a building.
Explanation:
An elevation is a three-dimensional, orthographic, architectural projection that reveals just a side of the building. It is represented with diagrams and shadows are used to create the effect of a three-dimensional image.
It reveals the position of the building from ground-depth and only the outer parts of the structure are illustrated. Elevations, building plans, and section drawings are always drawn together by the architects.