math5001_2023 programs

math5001_2023 programs,
programs, data, and plots for a lecture on Clustering Data with the K-Means Algorithm.

• faithful_data.txt, the original 272 pairs of eruption and wait times for a geyser.
• faithful_normalized.txt, the normalized data.
• faithful_standardized.txt, the standardized data.

• faithful_wait.py, make a histogram of the waiting times.
• faithful_both.py, plot eruption and wait times together, rescale the data, and write to new files.
faithful_guess.py, guess two centers, then cluster the data.
• faithful_lloyd.py, perform four iterations on Lloyd's clustering algorithm.
• faithful_kmeans.py, cluster the data with the scikit-learn kmeans() function.
• faithful_kmeans2.py, cluster the data with the scipy kmeans2() function.
• faithful_energy.py, plot the change in cluster energy as we increase the number of clusters.
• faithful_classify.py, use our model to classify new data.
• faithful_simulate.py, use our model to simulate new data.
• blobs_energy.py, plot the change in cluster energy as we increase the number of clusters for a set of "blobs" data.
• cluster_demo.py, run some illustrations for the cluster lecture.

• faithful_wait.png, a histogram of the waiting times.
• faithful_raw.png, a plot of the raw data.
• faithful_normalized.png, a plot of the normalized data.
• faithful_standardized.png, a plot of the standardized data.
• faithful_guess_centers.png, our guesses for cluster centers.
• faithful_guess_clusters.png, the clustering induced by our guessed cluster centers.
• faithful_lloyd_iteration0.png, Lloyd's iteration 0.
• faithful_lloyd_iteration1.png, Lloyd's iteration 1.
• faithful_lloyd_iteration2.png, Lloyd's iteration 2.
• faithful_lloyd_iteration3.png, Lloyd's iteration 3.
• faithful_kmeans.png, clustering with kmeans().
• faithful_kmeans2.png, clustering with kmeans2().
• faithful_energy.png, clustering energy with increasing k.
• faithful_classify.png, classifying new data.
• faithful_simulate.png, a new set of simulated data.
• blobs_cluster_one.png, applying one cluster to two blobs of data.
• blobs_data.png, a set of blob data.
• blobs_energy.png, the decrease in cluster energy with increasing k, for blob data.
• data_blobs.png, 100 points in "blobs".
• data_grid.png, 100 grid points in the unit square.
• data_normal.png, 100 normal random values with mean 0 and standard deviation 1.
• data_uniform.png, 100 random points in unit square.