Calculating Accuracy Score in Machine Learning using Python

by Amrita Mitra | Jan 13, 2023 | AI, Machine Learning and Deep Learning, Featured, Machine Learning Using Python, Python Scikit-learn, Statistics For Machine Learning

$Accuracy \ Score=\frac{TP + TN}{TP + TN + FP + FN}$

So, in our example,

TP = 4
TN = 4
FP = 1
FN = 1

So, the accuracy score is:

$Accuracy \ Score=\frac{TP + TN}{TP + TN + FP + FN}=\frac{4 + 4}{4 + 4 + 1 + 1} = \frac{8}{10} = 0.8$

How to calculate the accuracy score using the sklearn Python library?

We can use the following Python code to calculate the accuracy score of a machine learning model.

from sklearn.metrics import accuracy_score

Ya = [False, False, True, True, True, False, True, False, False, True]
Y = [True, False, True, True, False, False, True, False, False, True]

accuracy = accuracy_score(Ya, Y)
print("Accuracy Score: \n", accuracy)

Here, Ya is the actual or expected output. And Y is the calculated output. The output of the above program will be:

Accuracy Score: 
 0.8

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