How to find similar predicted x between 2 models?

Question

I have 2 models implemented with the same algorithm but with different number of features thus 2 different confusion matrix. I would like to see which predicted items are similar between those 2 and plot the similarity predicted in a Venn diagram.

Answer 1

Answer

data = {"Mod1":[1,0,1,1,0,0,0,1,1,1],"Mod2":[1,0,1,0,1,0,0,1,0,1]}

df = pd.DataFrame(data)
df["Similar"] = np.where(df["Mod1"]==df["Mod2"],1,0)
df.head()

#output

Mod1Mod2Similar
0   1   1   1
1   0   0   1
2   1   1   1
3   1   0   0
4   0   1   0

This should do the job Visualization

# !pip install matplotlib-venn

import matplotlib.pyplot as plt
from matplotlib_venn import venn2

venn2(subsets = (3, 3, 7), set_labels = ('Mod1', 'Mod2'))
plt.show()