stream (version 2.0-1)

get_assignment: Assignment Data Points to Clusters deprecated

Description

Deprecation Notice: use predict() for a more general interface to apply a data stream model to new data. get_assignment() is deprecated.

Usage

get_assignment(
  dsc,
  points,
  type = c("auto", "micro", "macro"),
  method = "auto",
  ...
)
# S3 method for DSC
get_assignment(
  dsc,
  points,
  type = c("auto", "micro", "macro"),
  method = c("auto", "nn", "model"),
  ...
)

Value

A vector containing the assignment of each point. NA means that a data point was not assigned to a cluster.

Arguments

dsc

The DSC object with the clusters for assignment.

points

The points to be assigned as a data.frame.

type

Use micro- or macro-clusters in DSC for assignment.

method

assignment method

• "model" uses the assignment method of the underlying algorithm (unassigned points return NA). Not all algorithms implement this option.

• "nn" performs nearest neighbor assignment using Euclidean distance.

• "auto" uses the model assignment method. If this method is not implemented/available then method "nn" is used instead.

...

Additional arguments are passed on.

Author

Michael Hahsler

Details

Get the assignment of data points to clusters in a DSC using the model's assignment rules or nearest neighbor assignment. The clustering is not modified.

Each data point is assigned either using the original model's assignment rule or Euclidean nearest neighbor assignment. If the user specifies the model's assignment strategy, but is not available, then nearest neighbor assignment is used and a warning is produced.

See Also

Other DSC: DSC_Macro(), DSC_Micro(), DSC_R(), DSC_SlidingWindow(), DSC_Static(), DSC_TwoStage(), DSC(), animate_cluster(), evaluate.DSC, plot.DSC(), predict(), prune_clusters(), read_saveDSC, recluster()

Examples

stream <- DSD_Gaussians(k = 3, d = 2, noise = .05)

dbstream <- DSC_DBSTREAM(r = .1)
update(dbstream, stream, n = 100)

# find the assignment for the next 100 points to
# micro-clusters in dsc. This uses the model's assignment function
points <- get_points(stream, n = 100)
a <- predict(dbstream, points)
head(a)

# show the MC assignment areas. Assigned points as blue circles and
# the unassigned points as red dots
plot(dbstream, stream, assignment = TRUE, type = "none")
points(points[!is.na(a[, ".class"]),], col = "blue")
points(points[is.na(a[, ".class"]),], col = "red", pch = 20)

# use nearest neighbor assignment instead
a <- predict(dbstream, points, method = "nn")
head(a)