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Remove depreciated np.float (#7394)

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Tianyi Zheng 2022-10-18 05:57:03 -04:00 committed by GitHub
parent 49cd46acea
commit 6d1e009f35
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1 changed files with 4 additions and 4 deletions
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machine_learning/decision_tree.py
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@ -24,13 +24,13 @@ class DecisionTree:
estimate the labels estimate the labels
>>> tester = DecisionTree() >>> tester = DecisionTree()
>>> test_labels = np.array([1,2,3,4,5,6,7,8,9,10]) >>> test_labels = np.array([1,2,3,4,5,6,7,8,9,10])
>>> test_prediction = np.float(6) >>> test_prediction = float(6)
>>> tester.mean_squared_error(test_labels, test_prediction) == ( >>> tester.mean_squared_error(test_labels, test_prediction) == (
... TestDecisionTree.helper_mean_squared_error_test(test_labels, ... TestDecisionTree.helper_mean_squared_error_test(test_labels,
... test_prediction)) ... test_prediction))
True True
>>> test_labels = np.array([1,2,3]) >>> test_labels = np.array([1,2,3])
>>> test_prediction = np.float(2) >>> test_prediction = float(2)
>>> tester.mean_squared_error(test_labels, test_prediction) == ( >>> tester.mean_squared_error(test_labels, test_prediction) == (
... TestDecisionTree.helper_mean_squared_error_test(test_labels, ... TestDecisionTree.helper_mean_squared_error_test(test_labels,
... test_prediction)) ... test_prediction))
@ -145,11 +145,11 @@ class TestDecisionTree:
@param prediction: a floating point value @param prediction: a floating point value
return value: helper_mean_squared_error_test calculates the mean squared error return value: helper_mean_squared_error_test calculates the mean squared error
""" """
squared_error_sum = np.float(0) squared_error_sum = float(0)
for label in labels: for label in labels:
squared_error_sum += (label - prediction) ** 2 squared_error_sum += (label - prediction) ** 2
return np.float(squared_error_sum / labels.size) return float(squared_error_sum / labels.size)
def main(): def main():