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Update app.py
Browse files
app.py
CHANGED
@@ -106,7 +106,7 @@ def do_train(n_samples, n_new_data):
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probable_clusters = inductive_learner.predict(X_new)
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fig3, axes3 = plt.subplots()
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disp = DecisionBoundaryDisplay.from_estimator(
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inductive_learner,
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)
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disp.ax_.set_title("Classify unknown instances with known clusters")
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disp.ax_.scatter(X[:, 0], X[:, 1], c=cluster_labels, alpha=0.5, edgecolor="k")
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@@ -120,7 +120,7 @@ def do_train(n_samples, n_new_data):
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classifier = RandomForestClassifier(random_state=RANDOM_STATE).fit(X_all, y)
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fig4, axes4 = plt.subplots()
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disp = DecisionBoundaryDisplay.from_estimator(
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classifier,
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)
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disp.ax_.set_title("Classify unknown instance with recomputing clusters")
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disp.ax_.scatter(X_all[:, 0], X_all[:, 1], c=y, alpha=0.5, edgecolor="k")
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probable_clusters = inductive_learner.predict(X_new)
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fig3, axes3 = plt.subplots()
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disp = DecisionBoundaryDisplay.from_estimator(
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inductive_learner, X, response_method="predict", alpha=0.4, ax=axes3
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)
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disp.ax_.set_title("Classify unknown instances with known clusters")
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disp.ax_.scatter(X[:, 0], X[:, 1], c=cluster_labels, alpha=0.5, edgecolor="k")
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classifier = RandomForestClassifier(random_state=RANDOM_STATE).fit(X_all, y)
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fig4, axes4 = plt.subplots()
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disp = DecisionBoundaryDisplay.from_estimator(
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classifier, X_all, response_method="predict", alpha=0.4, ax=axes4
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)
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disp.ax_.set_title("Classify unknown instance with recomputing clusters")
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disp.ax_.scatter(X_all[:, 0], X_all[:, 1], c=y, alpha=0.5, edgecolor="k")
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