June 2020
Intermediate to advanced
382 pages
11h 39m
English
Content preview from 40 Algorithms Every Programmer Should Know
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The steps of the k-means algorithm
The steps involved in the k-means clustering algorithm are as follows:
| Step 1 | We choose the number of clusters, k. |
| Step 2 | Among the data points, we randomly choose k points as cluster centers. |
| Step 3 | Based on the selected distance measure, we iteratively compute the distance from each point in the problem space to each of the k cluster centers. Based on the size of the dataset, this may be a time-consuming step—for example, if there are 10,000 points in the cluster and k = 3, this means that 30,000 distances need to be calculated. |
| Step 4 | We assign each data point in the problem space to the nearest cluster center. |
| Step 5 | Now each data point in our problem space has an assigned cluster center. ... |
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