diff options
| -rw-r--r-- | run.R | 25 |
1 files changed, 15 insertions, 10 deletions
@@ -352,11 +352,13 @@ run.manipulation.evo <- function(X, Dx, labels, sample.indices, k, ds, output.di # Perform manipulation loginfo("Running manipulation procedures") - loginfo("Ys.f: Silhouette") - Dx.m <- automated.silh(X[sample.indices, ], labels[sample.indices]) - Ys.silhouette <- scale.Ys(cmdscale(Dx.m)) - Ys.m <- Ys.silhouette - write.table(Ys.m, file.path(output.dir, ds$name, "Ysf-silhouette.tbl"), row.names=F, col.names=F) + if (!is.null(ds$labels.file)) { + loginfo("Ys.f: Silhouette") + Dx.m <- automated.silh(X[sample.indices, ], labels[sample.indices]) + Ys.silhouette <- scale.Ys(cmdscale(Dx.m)) + Ys.m <- Ys.silhouette + write.table(Ys.m, file.path(output.dir, ds$name, "Ysf-silhouette.tbl"), row.names=F, col.names=F) + } loginfo("Ys.f: NP") Ys.np <- scale.Ys(Rtsne(X[sample.indices, ], perplexity=k)$Y) @@ -384,7 +386,9 @@ run.technique.evo <- function(X, Dx, labels, k, ds, tech, n.samples, output.dir) loginfo("Technique: %s", tech$name) dir.create.safe(file.path(output.dir, ds$name, tech$name)) - classes <- as.factor(labels) + if (!is.null(ds$labels.file)) { + classes <- as.factor(labels) + } # Load sample indices... sample.indices <- read.table(file.path(output.dir, ds$name, "sample-indices.tbl"))$V1 @@ -608,7 +612,7 @@ run.evo <- function(datasets, Dx <- as.matrix(Dx) loginfo("Extracting control points") - sample.indices <- extract.CPs(Dx) + sample.indices <- extract.CPs(Dx, k=max(sqrt(n)*3, ncol(X))) write.table(sample.indices, file.path(output.dir, ds$name, "sample-indices.tbl"), row.names=F, col.names=F) # Computes each manipulation target @@ -738,9 +742,10 @@ addHandler(writeToFile, file=args[1], level="FINEST") -# The alpha and omega +# CP positioning improvement run(datasets, techniques, output.dir=output.dir, initial.manipulation=F) -run.evo(datasets, techniques, output.dir=output.dir) - # Compute all confidence intervals confidence.intervals(datasets, techniques, measures, output.dir) + +# CP improvement evolution experiment +run.evo(datasets, techniques, output.dir=output.dir) |