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rEMM (version 1.0-7)

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

676

Version

1.0-7

License

GPL-2

Maintainer

Michael Hahsler

Last Published

August 11th, 2013

Functions in rEMM (1.0-7)

EMMTraffic

Hypothetical Traffic Data Set for EMM
TRACDS-class

Class "TRACDS"
remove

Remove States/Clusters or Transitions from an EMM
combine

Combining EMM Objects
synthetic_stream

Create a Synthetic Data Stream
predict

Predict a Future State
Derwent

Derwent Catchment Data
EMMsim

Synthetic Data to Demonstrate EMMs
build

Building an EMM using New Data
transition_table

Extract a Transition Table for a New Sequence Given an EMM
find_clusters

Find the EMM State/Cluster for an Observation
prune

Prune States and/or Transitions
EMM

Creator for Class "EMM"
plot

Visualize EMM Objects
merge_clusters

Merge States of an EMM
transition

Access Transition Probabilities/Counts in an EMM
update

Update a TRACDS temporal structure with new state assignements
EMM-class

Class "EMM"
fade

Fading Cluster Structure and EMM Layer
recluster

Reclustering EMM states
TRAC

TRAC: Creating an EMM from a Regular Clustering
cluster

Data stream clustering with tNN
tNN-class

Class "tNN"
16S

Count Data for 16S rRNA Sequences
score

Score a New Sequence Given an EMM