Finding the euclidean distance with SciPy
Instead of writing multiple lines of code to calculate the euclidean distance, you can use SciPy. The library not only contains the euclidean
function, but more than 40 other distance metrics—all a single import statement away.
This exercise is part of the course
Anomaly Detection in Python
Exercise instructions
- Import the
euclidean
function from the relevantscipy
module. - Use the
euclidean()
function onM
andN
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Import the euclidean function from scipy
from scipy.____.____ import euclidean
M = np.array([14, 17, 18, 20, 14, 12, 19, 13, 17, 20])
N = np.array([63, 74, 76, 72, 64, 75, 75, 61, 50, 53])
# Use the euclidean function on M and N
dist_MN = ____
print(dist_MN)