Final answer:
In K-means algorithm with lı norm, we use the median instead of the mean when calculating the centroid. The median is more robust to outliers and extreme values, making it a better measure of the center.
Step-by-step explanation:
In K-means algorithm with lı norm, when calculating the centroid, we use the median instead of the mean. The mean is the average of a set of values, while the median is the middle value when the data is sorted in ascending order. The median is more robust to outliers and extreme values, making it a better measure of the center when there are such values present.
For example, let's say we have a data set of {1, 2, 3, 4, 100}. The mean would be (1 + 2 + 3 + 4 + 100)/5 = 22, while the median would be 3. In this case, the median better represents the center of the data as it is not affected by the outlier value of 100.