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Refactor tests
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20
sample.py
20
sample.py
@@ -69,13 +69,14 @@ for proposed in [True, False]:
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X = data.data
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y = data.target
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print("*** Proposed: ", proposed)
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test = CFImdlp(debug=False, proposed=proposed)
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test = CFImdlp(debug=True, proposed=proposed)
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test.fit(X[:, 0], y)
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result = test.get_cut_points()
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for item in result:
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print(
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f"Class={item['classNumber']} - ({item['start']:3d}, {item['end']:3d})"
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f" -> ({item['fromValue']:3.1f}, {item['toValue']:3.1f}]"
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f"Class={item['classNumber']} - ({item['start']:3d}, "
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f"{item['end']:3d}) -> ({item['fromValue']:3.1f}, "
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f"{item['toValue']:3.1f}]"
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)
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print(test.get_discretized_values())
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print("+" * 40)
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@@ -114,11 +115,14 @@ for proposed in [True, False]:
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# # k = test.cut_points_ant(X[:, 0], y)
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# # print(k)
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# # test.debug_points(X[:, 0], y)
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X = [5.7, 5.3, 5.2, 5.1, 5.0, 5.6, 5.1, 6.0, 5.1, 5.9]
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indices = [4, 3, 6, 8, 2, 1, 5, 0, 9, 7]
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# X = [5.7, 5.3, 5.2, 5.1, 5.0, 5.6, 5.1, 6.0, 5.1, 5.9]
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# y = [1, 1, 1, 1, 1, 2, 2, 2, 2, 2]
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# indices = [4, 3, 6, 8, 2, 1, 5, 0, 9, 7]
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# clf = CFImdlp(debug=True, proposed=False)
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# clf.fit(X, y)
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# print(clf.get_cut_points())
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# y = [1, 1, 1, 1, 1, 2, 2, 2, 2, 2]
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# # To check
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# indices2 = np.argsort(X)
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Xs = np.array(X)[indices2]
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ys = np.array(y)[indices2]
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# Xs = np.array(X)[indices2]
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# ys = np.array(y)[indices2]
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