EdgeClassifier 0.0.11

A python package for classify edges of graph based on topological features and neural networks.

Edge Prediction

Graph's edges classification by topological (and other) features with neural network.

Installation

• Installation via pip:

pip install

• Installation with git:

git clone https://github.com/louzounlab/Edge-Prediction.git

How to use?

import networkx as nx
from EdgeClassifier.edge_classifier import EdgeClassifier

# Build networkx graph from edges list:
graph = nx.read_edgelist("./data/graph1.txt", delimiter=",", create_using=nx.DiGraph,
                         data=(("label", int), ("attribute1", float,)))
graph = nx.convert_node_labels_to_integers(graph)

# Build the classifier.
classifier = EdgeClassifier("./pkl", "./plots", verbose=True, gpu=False)

# Define parameters to the graph and to the model and execute.
classifier.build("graph5", graph, {
    "lr": 0.001,
    "batch_size": 64,
    "epochs": 150
}, topological_features=None, data_features=["attribute1"])

This package classify graphs' edges by , graph edges classification by topological attributes

Attention! This package uses non boost graph-measures, and that's might make the features calculation slower. If you would like to clac them in boost environment, follow the instruction here (link), and move th .pkl file to the pkl directory.