Added a bit of padding to prevent label from overlapping graph title.
Browse files
app.py
CHANGED
@@ -15,12 +15,13 @@ def initial_points(X, y_true, n_components, n_clust):
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centers_init, indices = kmeans_plusplus(X, n_clusters=n_clust, random_state=0)
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# Plot init seeds along side sample data
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init_points_plot = plt.
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for k in range(n_components):
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cluster_data = y_true == k
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plt.scatter(X[cluster_data, 0], X[cluster_data, 1], marker=".", s=10)
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plt.scatter(centers_init[:, 0], centers_init[:, 1], c="b", s=50)
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plt.title("K-Means++ Initialization")
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plt.xticks([])
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@@ -31,11 +32,12 @@ def one_step(X, n_clust):
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kmeans = KMeans(n_clusters=n_clust, max_iter=1, n_init=1, random_state=0).fit(X)
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y_hat = kmeans.predict(X)
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one_step = plt.
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plt.scatter(X[:, 0], X[:, 1], marker=".", s=10, c=y_hat)
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centers = kmeans.cluster_centers_
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plt.scatter(centers[:, 0], centers[:, 1], c="b", s=50)
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plt.title("K-Means After One Step")
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plt.xticks([])
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plt.yticks([])
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centers_init, indices = kmeans_plusplus(X, n_clusters=n_clust, random_state=0)
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# Plot init seeds along side sample data
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+
init_points_plot, ax = plt.subplots()
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for k in range(n_components):
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cluster_data = y_true == k
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plt.scatter(X[cluster_data, 0], X[cluster_data, 1], marker=".", s=10)
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plt.subplots_adjust(top=0.8)
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plt.scatter(centers_init[:, 0], centers_init[:, 1], c="b", s=50)
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plt.title("K-Means++ Initialization")
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plt.xticks([])
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kmeans = KMeans(n_clusters=n_clust, max_iter=1, n_init=1, random_state=0).fit(X)
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y_hat = kmeans.predict(X)
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one_step, ax = plt.subplots()
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plt.scatter(X[:, 0], X[:, 1], marker=".", s=10, c=y_hat)
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centers = kmeans.cluster_centers_
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plt.scatter(centers[:, 0], centers[:, 1], c="b", s=50)
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plt.subplots_adjust(top=0.8)
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plt.title("K-Means After One Step")
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plt.xticks([])
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plt.yticks([])
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