| linkage.getresults {Linkage} | R Documentation |
Retrieve results for a specific job.
Description
Retrieve results for a specific job posted on the Linkage.fr server.
Usage
linkage.getresults(job_id, token)
Arguments
job_id |
The id of the job to retrieve (as returned by the linkage.post or the linkage.check functions). |
token |
The token of the user. This personal token can be found on https://linkage.fr/developers/ after registration. Registration is free of charge for individual and academic users. |
Value
It returns a list containing in particular:
job_id |
the job id |
nb_nodes |
the number of nodes |
nb_edges |
the number of edges |
clusters_optim |
the optimal number of clusters |
topics_optim |
the optimal number of topics |
dictionary |
the list of words used in the texts |
result |
a list containing the clustering results for the optimal numbers of clusters and topics. This list contains in particular: - clusters_mat: clustering of the nodes - rho_mat: node cluster proportions - pi_mat: estimated connexion probabilities between clusters - theta_qr_mat: estimated proportions of topics in interactions between groups - top_words: most representative words for each topic |
Author(s)
Charles Bouveyron <charles.bouveyron@gmail.com>
References
C. Bouveyron, P. Latouche and R. Zreik, The Stochastic Topic Block Model for the Clustering of Networks with Textual Edges, Statistics and Computing, vol. 28(1), pp. 11-31, 2017 <doi:10.1007/s11222-016-9713-7>
Examples
## Not run:
data(Enron)
write.table(Enron, file="Enron.csv",row.names=FALSE,col.names=FALSE, sep=",")
file = "Enron.csv"
# Provide the user token, which is provided on "developers" page
# of http://linkage.fr (after registration)
token = "xxxxxxxxxxxxxxxxxxxx"
# Post the job
job_id = linkage.post(file, token, job_title="My job: Enron",
clusters_min = 8, clusters_max = 8,
topics_min = 6,topics_max = 6,
filter_largest_subgraph = TRUE)
# Monitor achievment of the current job
ans = linkage.check(token)
# Retrieve results (once achievment is 100
res = linkage.getresults(job_id,token)
# Plot the results
plot(res,type='all')
## End(Not run)