Link Prediction in Social Netowork

:info: A perfect repo for your college project on data mining - link prediction - friends recommender.

How To Use

#.

.. code-block:: shell

    pip install networkx
     

#.

To run and understand this code  first reach ___EntryPoint___ in `python code <https://github.com/iamsinghrajat/Friends-Recommender-In-Social-Network/blob/9c0f4516123c8a5dd3163718704b375ab1c2c7da/LinkPredictionInSocialNetwork.py#L264>`_ . 

#.

* facebook_combine.txt is dataset.

* Facebook dataset is included download others from http://snap.stanford.edu/data/ . Use one with format like twitter_combine.txt or gplus_combine.txt .

* At entry point you can choose which dataset to use you can even add your own dataset from http://snap.stanford.edu/data/ . Code will work for all dataset.

*  By default it is set to Facebook Data Set

#. * sample_positive.txt: all positive friend relation ie. people with connecting edge in graph * sample_negative.txt: all negative friend relation ie. people with no connecting edge in graph * training.txt: combination of positive and negative to get a dataset of relations * features_combined_2.txt: for each relation features like AdamicAdar are calculated and then used for training model

#. Following Scoring Methods are used to construct feature Set

* common_neighbors

* resource_allocation_index

* jaccard_coefficient

* adamic_adar_index

* preferential_attachment

#. SVM ANN and Logistic Regresssion is used for classificaion