机器学习作业

机器学习作业(第十八次课堂作业) 题

按照课堂所示范例逐步计算（画出各种表）如下多分类的Micro（微）, Macro （宏）& Weighted Averages （加权） F1 Score、Recall、precision，和混淆矩阵（confusion matrix）。并用sklearn编程验证你的手动计算。

手动计算

sklearn编程验证

import numpy as np 
from sklearn.metrics import precision_score, recall_score, f1_score
Actual = np.array(['cat', 'cat', 'cat', 'cat', 'dog', 'dog', 'dog', 'bird', 'bird'])
Predicted= np.array(['cat', 'cat', 'cat', 'cat', 'dog', 'dog', 'cat', 'dog', 'bird'])
print(recall_score(Actual, Predicted, average = 'micro'))
print(precision_score(Actual, Predicted, average = 'micro'))
print(f1_score(Actual, Predicted, average = 'micro'))
print(recall_score(Actual, Predicted, average = 'macro'))
print(precision_score(Actual, Predicted, average = 'macro'))
print(f1_score(Actual, Predicted, average = 'macro'))
print(recall_score(Actual, Predicted, average = 'weighted'))
print(precision_score(Actual, Predicted, average = 'weighted'))
print(f1_score(Actual, Predicted, average = 'weighted'))

验证结果

结果与心得

macor与weighted在f1_score上存在数据不一致现象(原因尚未找到)，其他数据结果一致。
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