A linear decision boundary in one dimension, of course, can be described by a rule ofthe form ifX 1> cthenY= 1, else= 0, wherecis a real-valued threshold (seediagram provided). Is it possible in this simple one-dimensional case to construct a Gaussian Naive Bayes classifier with a decision boundary that cannot be expressed bya rule in the above form)

An equation representing lyle’s hedge-trimming business is a = 12n - 300 where a is the amount of profit or loss in dollars and n is the number of hedges trimmed. how would the graph of lyle’s business change if the equation a = 10n - 300 represented his business? the graph would be flatter. the graph would be steeper. the graph would start closer to the origin. the graph would start lower on the y-axis.

41/17 as a decimal rounded to the nearest hundredth

Which of the following values are in the range of the function graphed below? check all that apply ! - will give the answer "brainliest! "