> For the complete documentation index, see [llms.txt](https://vikram-bajaj.gitbook.io/deep-learning-specialization-coursera/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://vikram-bajaj.gitbook.io/deep-learning-specialization-coursera/main-10/convolutional-neural-networks/face-recognition/face-recognition-as-binary-classification.md).

# Face Recognition as Binary Classification

Face Recognition can also be looked at as a binary classification problem.

We know that the Siamese Network outputs a pair of encodings, one for each image.

These encodings can be used to train a Logistic Regression classifier with labels 0 (not same person) and 1 (same person), instead of using the triplet loss function for training.

The Logistic Regression equation for this problem would be:

$$\hat{y} = \sigma (\sum\_{k=1}^{num\_features} w\_i |f(x^{(i)})\_k-f(x^{(j)})\_k| + b)$$