-
subset of columns, or vice versa.
Biclustering was
originally introduced by John A.
Hartigan in 1972. The term "
Biclustering" was then
later used and refined...
-
covarying genes. A
combination of both
clustering approaches,
known as
biclustering, has been used to
simultaneously cluster by
genes and
cells to find genes...
- a
formal concept.
Relaxed FCA-based
versions of
biclustering and
triclustering include OA-
biclustering and OAC-triclustering (here O
stands for object...
- architecture, but also in meta-learning,
reinforcement learning and
biclustering with
application to
bioinformatics data.
Hochreiter developed the long...
-
Animation of the
topic detection process in a do****ent-word
matrix through biclustering.
Every column corresponds to a do****ent,
every row to a word. A cell...
-
clustering algorithms,
including the
famous Hartigan-Wong
method and
biclustering, and
Bayesian statistics.
Hartigan was born in Sydney,
Australia and...
-
Identification of
Local Patterns in the NBA
Performance Indicators".
Applied Biclustering Methods for Big and High-Dimensional Data
Using R. CRC Press. p. 298...
-
clusters as
connected dense regions in the data space.
Subspace models: in
biclustering (also
known as co-clustering or two-mode-clustering),
clusters are modeled...
-
disjoint union of cliques; Tanay,
Sharan &
Shamir (2002)
discuss a
similar biclustering problem for
expression data in
which the
clusters are
required to be...
- find
clusters based on
pattern in the data matrix,
often referred to as
biclustering,
which is a
technique frequently utilized in bioinformatics. Subspace...
