I am looking for a way of calculating how close data points are to a specified point in a $k$-dimensional space. My current method involves Pythagorean to calculate the distance between the specified point and each of the data points. However, when working with an order of $10,000$ data points this is very computationally intensive and is too slow for my program. Does anyone have suggestions for an alternative algorithm to use to determine a point's proximity to other data?
Thanks in advance