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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Data Set composition
iris data set
DESCR
Step1:  Recap - Decision Tree Classifier
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Python Code:
print(iris.DESCR[:172] + ' ...')
print(iris.feature_names)
print(iris.data[45:54])
print(iris.target[45:54])
print(iris.target_names)
Explanation: Data Set composition
iris data set
DESCR: ASCII Text description of the data
data: The source data in array
feature_names: The name of the attributes in the data
target: The target values in an array
target_names: Descriptions for the target values
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lfeat = iris.feature_names
df_iris = pd.DataFrame(iris.data, columns = lfeat)
model = DecisionTreeClassifier()
data = df_iris[lfeat].values
df_iris["Species"] = iris.target
target = df_iris["Species"].values
model.fit(data, target)
expected = target
predicted = model.predict(data)
print(metrics.classification_report(expected, predicted))
print(metrics.confusion_matrix(expected, predicted))
Explanation: Recap - Decision Tree Classifier
End of explanation
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