The key purpose of splitting the dataset into training and test sets is:

a. To speed up the training process

b. To reduce the amount of labeled data needed for evaluating classifier accuracy

c. To estimate how well the learned model will generalize to new data

d. To reduce the number of features we need to consider as input to the learning

me i beg !

step-by-step explanation:

check above link.

graphically?   well, you graph them both, the solutions is where they both intersect each other, since there are two solutions, meaning they will meet twice, or namely the linear will run into the quadratic curve twice, and where they meet, those x,y coordinates are the solutions to the system.

the one below it is a function