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25 lines
686 B
25 lines
686 B
import sklearn.cluster as cluster
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import pandas as pd
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from matplotlib import pyplot as plt
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def find_kmeans(mat, k, first, second):
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km = cluster.KMeans(n_clusters=k)
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km.fit(mat)
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# Plot sse against k
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plt.figure(figsize=(6, 6))
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plt.xlabel('Metric: ' + first)
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plt.ylabel('Metric: ' + second)
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plt.scatter(mat[:, 0], mat[:, 1], c=km.labels_, cmap='rainbow')
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plt.show()
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# Read csv in
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df = pd.read_csv('../data_preparation/cleaned/time_series_normalized_wellness_menstruation.csv')
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# Specify what things you want
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df = df[["normFatigue", "normSleepQuality"]]
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# values, num clusters, axis labelsg
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find_kmeans(df.values, 2, "normFatigue", "normSleepQuality")
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