Facebook-friend-recommedation

Machine learning model to recommend Facebook friend's

Problem statement:

Given a directed social graph, we have to predict missing links to recommend friends/connnections/followers (Link Prediction in graph).

Data Overview

Dataset from facebook's recruting challenge on kaggle: https://www.kaggle.com/c/FacebookRecruiting Data contains two columns: source and destination edge pairs in the directed graph.

Data columns (total 2 columns):

source_node int64 destination_node int64

Business objectives and constraints:

No low-latency requirements.

Predciting the probability of a link is useful so as to recommend the highest probability links to a user.

We got to suggest connnections which are most likley to be correct and we should try and not miss out any connnections.

Performance metric for supervised learning:

Both precision and recall are important, hence F1 score is good choice

Confusion matrix

Accuracy can also be checked