Creating confusion matrix from multiple .csv files

Question

I have a lot of .csv files with the following format.

338,800
338,550
339,670
340,600 
327,500
301,430
299,350
284,339
284,338
283,335
283,330
283,310
282,310
         


        

Answer 1

Using Scikit-Learn is the best option to go for in your case as it provides a confusion_matrix function. Here is an approach you can easily extend.

from sklearn.metrics import confusion_matrix

# Read your csv files
with open('A1.csv', 'r') as readFile:
    true_values = [int(ff) for ff in readFile]
with open('B1.csv', 'r') as readFile:
    predictions = [int(ff) for ff in readFile]

# Produce the confusion matrix
confusionMatrix = confusion_matrix(true_values, predictions)

print(confusionMatrix)

This is the output you would expect.

[[0 2]
 [0 2]]

For more hint - check out the following link:

How to write a confusion matrix in Python?