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ffm-baseline
Commit 41f521c6 authored by 王志伟's avatar 王志伟
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数据指标波动假设检验统计

parent a3317298
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eda/recommended_indexs/hypothesis_test.py
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...@@ -97,6 +97,7 @@ def t_test(x,y): #进行t检验 ...@@ -97,6 +97,7 @@ def t_test(x,y): #进行t检验
if p_value>0.05: #认为数据方差具有齐性，equal_var=ture if p_value>0.05: #认为数据方差具有齐性，equal_var=ture
t_test=ttest_ind(x,y,equal_var=True) t_test=ttest_ind(x,y,equal_var=True)
t_p_value=t_test[1] t_p_value=t_test[1]
print(t_p_value)
if t_p_value>0.05: if t_p_value>0.05:
print("策略前后两组数据无显著性差异，即该指标没有显著提升，p_value:%f" % t_p_value) print("策略前后两组数据无显著性差异，即该指标没有显著提升，p_value:%f" % t_p_value)
else: else:
...@@ -104,6 +105,7 @@ def t_test(x,y): #进行t检验 ...@@ -104,6 +105,7 @@ def t_test(x,y): #进行t检验
else: #认为数据方差不具有齐性，equal_var=false else: #认为数据方差不具有齐性，equal_var=false
t_test = ttest_ind(x, y, equal_var=False) t_test = ttest_ind(x, y, equal_var=False)
t_p_value = t_test[1] t_p_value = t_test[1]
print(t_p_value)
if t_p_value > 0.05: if t_p_value > 0.05:
print("策略前后两组数据无显著性差异，即该指标没有显著提升，p_value:%f" % t_p_value) print("策略前后两组数据无显著性差异，即该指标没有显著提升，p_value:%f" % t_p_value)
else: else:
......
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