Simple Genetic Algorithm (SGA) as feature selector, route optimization for home care service with SGA and semantic segmentation using Multiobjective Genetic Algorithm (MOGA)
When clustering, the clusters do not have the same patients throughout iterations. Looks like it converges to different results each time, which it should not do.
Anyhow, it should also select the n_clusters automatically, using the elbow method: computing the sum of squared distances between each point and its assigned centroid for different values of k (the number of clusters), and then plotting these values against k. The "elbow" in the plot is the value of k where the rate of decrease in the sum of squared distances starts to level off.
When clustering, the clusters do not have the same patients throughout iterations. Looks like it converges to different results each time, which it should not do.
Anyhow, it should also select the n_clusters automatically, using the elbow method: computing the sum of squared distances between each point and its assigned centroid for different values of k (the number of clusters), and then plotting these values against k. The "elbow" in the plot is the value of k where the rate of decrease in the sum of squared distances starts to level off.