<｜begin▁of▁sentence｜>### Instruction:
Imagine you're leading a sales team and you've outlined a network of contacts where connections represent conflicts of interest. The contacts are represented as points, specifically 0 through 5, and the conflicts are pairs: (0, 1), (0, 2), (1, 2), (2, 3), (3, 4), (4, 5). To maximize the potential of your sales strategy, you want to identify the largest group of contacts that have no conflicts with one another, essentially an independent set where none of the points are directly connected. Using the sophisticated analysis tools available in NetworkX, how would you determine the largest possible group of these non-conflicting contacts, often referred to as the maximum independent set, albeit via an approximation given the computational complexity of the problem?
### Response:
import networkx as nx
from networkx.algorithms import approximation

# Create a graph
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (1, 2), (2, 3), (3, 4), (4, 5)])

# Compute the approximate maximum independent set
max_indep_set = approximation.maximum_independent_set(G)
print("Approximate maximum independent set:", max_indep_set)
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