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rEMM (version 1.0-5)

Extensible Markov Model (EMM) for Data Stream Clustering in R

Description

This package implements TRACDS (Temporal Relationships between Clusters for Data Streams) which is a generalization of Extensible Markov Model (EMM). TRACDS adds a temporal or order model to data stream clustering by superimposing a dynamically adapting Markov Chain. This package implements EMM (TRACDS on top of tNN data stream clustering). Development of this package was supported in part by NSF IIS-0948893 and R21HG005912 from the National Human Genome Research Institute.

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Version

Install

install.packages('rEMM')

Monthly Downloads

674

Version

1.0-5

License

GPL-2

Maintainer

Michael Hahsler

Last Published

April 9th, 2012

Functions in rEMM (1.0-5)

combine

Combining EMM Objects
build

Building an EMM using New Data
TRAC

TRAC: Creating an EMM from a regulat clustering
plot

Visualize EMM Objects
transition

Access Transition Probabilities/Counts in an EMM
transition_table

Extract a Transition Table for a New Sequence Given an EMM
TRACDS-class

Class "TRACDS"
predict

Predict a Future State
tNN-class

Class "tNN"
EMMTraffic

Hypothetical Traffic Data Set for EMM
score

Score a New Sequence Given an EMM
cluster

Data stream clustering with tNN
recluster

Reclustering EMM states
synthetic_stream

Create a Synthetic Data Stream
merge_clusters

Merge States of an EMM
fade

Fading Cluster Structure and EMM Layer
16S

Count Data for 16S rRNA Sequences
prune

Prune States and/or Transitions
EMM

Creator for Class "EMM"
update

Update a TRACDS temporal structure with new state assignements
find_clusters

Find the EMM State/Cluster for an Observation
Derwent

Derwent Catchment Data
EMM-class

Class "EMM"
remove

Remove States/Clusters or Transitions from an EMM
EMMsim

Synthetic Data to Demonstrate EMMs