To classify a new point, K$-$NN can be slow. Why does it take so long?

Group of answer choices

The K$-$NN algorithm fits a model to the data, which takes more time than simply measuring the distances between points.

The K$-$NN algorithm creates a matrix for each data point, then applies that to the test point$($s$).$

The K$-$NN algorithm assigns each data point its own category.

The K$-$NN algorithm computes the distances from the test point$($s$)$ to all data points.