get.cluster: Final estimators of the community labels
In FusedPCA: Community Detection via Fused Principal Component Analysis

Get the final estimator of the community labels along the path, according to ratio cut or normalised cut criterion.

1	get.cluster(A, iso.seq, cut.list, clusters.list, mod.list)

`A`	input matrix – the adjacency matrix of the observed graph. Notice, both isolated and non-isolated nodes are included.
`iso.seq`	a vector of the indices of the isolated nodes. It can be generated by `isolate`.
`cut.list`	the ratio cut and normalised cut value lists along the path. Notice, only meaningful values are input. For details, please see the listed paper. It can be generated by `fpca.cut`.
`clusters.list`	the estimators of the community labels along the path. It can be generated by `fpca.cluster`.
`mod.list`	the modularity value lists based on the DCBM and SBM assumptions along the path. Notice, only meaningful values are input. For details, please see the listed paper. It can be generated by `fpca.mod`.

`final.ratio.cluster`	the final estimator of the community labels according to the ratio cut criterion.
`ratio.location`	the location of the chosen estimator on the path according to the ratio cut criterion.
`final.normalised.cluster`	the final estimator of the community labels according to the normalised cut criterion.
`normalised.location`	the location of the chosen estimator on the path according to the normalised cut criterion.