hikmeans.h File Reference

Hierachical integer K-Means clustering. More...

#include "generic.h"
#include "ikmeans.h"

Go to the source code of this file.

Data Structures
struct	_VlHIKMNode
	HIKM tree node. More...
struct	_VlHIKMTree
	HIKM tree. More...
Functions
Create and destroy
VlHIKMTree *	vl_hikm_new (int method)
	New HIKM tree.
void	vl_hikm_delete (VlHIKMTree *f)
	Delete HIKM tree.
Retrieve data and parameters
VL_INLINE int	vl_hikm_get_ndims (VlHIKMTree const *f)
	Get data dimensionality.
VL_INLINE int	vl_hikm_get_K (VlHIKMTree const *f)
	Get K.
VL_INLINE int	vl_hikm_get_depth (VlHIKMTree const *f)
	Get depth.
VL_INLINE int	vl_hikm_get_verbosity (VlHIKMTree const *f)
	Get verbosity level.
VL_INLINE int	vl_hikm_get_max_niters (VlHIKMTree const *f)
	Get maximum number of iterations.
VL_INLINE VlHIKMNode const *	vl_hikm_get_root (VlHIKMTree const *f)
	Get maximum number of iterations.
Set parameters
VL_INLINE void	vl_hikm_set_verbosity (VlHIKMTree *f, int verb)
	Set verbosity level.
VL_INLINE void	vl_hikm_set_max_niters (VlHIKMTree *f, int max_niters)
	Set maximum number of iterations.
Process data
void	vl_hikm_init (VlHIKMTree *f, int M, int K, int depth)
	Initialize HIKM tree.
void	vl_hikm_train (VlHIKMTree *f, vl_ikm_data const *data, int N)
	Train HIKM tree.
void	vl_hikm_push (VlHIKMTree *f, vl_uint *asgn, vl_ikm_data const *data, int N)
	Project data down HIKM tree.

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Detailed Description

Heirachical Integer K-Means Clustering.

Hierarichial integer K-Means clustering (HIKM) is a simple hierarchical version of integer K-Means (IKM). The algorithm recusrively apply integer K-means to create more refined partitions of the data.

Use the vl_hikm() function to partition the data and create a HIKM tree (and vl_hikm_delete() to dispose of it). Use vl_hikm_push() to project new data down a HIKM tree.

HIKM tree

The HIKM tree is a simple structure, represented by VlHIKMTree and VlHIKMNode. The tree as a

Author:

Brian Fulkerson

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Function Documentation

void vl_hikm_delete

(

VlHIKMTree *

f

)

Parameters:

f

HIKM tree.

VL_INLINE int vl_hikm_get_depth

(

VlHIKMTree const *

f

)

Parameters:

f

HIKM tree.

Returns:

depth.

VL_INLINE int vl_hikm_get_K

(

VlHIKMTree const *

f

)

Parameters:

f

HIKM tree.

Returns:

K.

VL_INLINE int vl_hikm_get_max_niters

(

VlHIKMTree const *

f

)

Parameters:

f

HIKM tree.

Returns:

maximum number of iterations.

VL_INLINE int vl_hikm_get_ndims

(

VlHIKMTree const *

f

)

Parameters:

f

HIKM tree.

Returns:

data dimensionality.

VL_INLINE VlHIKMNode const * vl_hikm_get_root

(

VlHIKMTree const *

f

)

Parameters:

f

HIKM tree.

Returns:

maximum number of iterations.

VL_INLINE int vl_hikm_get_verbosity

(

VlHIKMTree const *

f

)

Parameters:

f

HIKM tree.

Returns:

verbosity level.

void vl_hikm_init	(	VlHIKMTree *	f,
		int	M,
		int	K,
		int	depth
	)

Parameters:

	f	HIKM tree.
	M	Data dimensionality.
	K	Number of clusters per node.
	depth	Tree depth.

Remarks:

depth cannot be smaller than 1.

Returns:

a new HIKM tree representing the clustering.

VlHIKMTree* vl_hikm_new

(

int

method

)

Parameters:

method

clustering method.

Returns:

new HIKM tree.

void vl_hikm_push	(	VlHIKMTree *	f,
		vl_uint *	asgn,
		vl_ikm_data const *	data,
		int	N
	)

Parameters:

	f	HIKM tree.
	asgn	Path down the tree (out).
	data	Data to project.
	N	Number of data.

The function writes to asgn the path of the data data down the HIKM tree f. The paramter asgn must point to an array of M by N elements, where M is the depth of the HIKM tree and N is the number of data point to process.

VL_INLINE void vl_hikm_set_max_niters	(	VlHIKMTree *	f,
		int	max_niters
	)

Parameters:

	f	HIKM tree.
	max_niters	maximum number of iterations.

VL_INLINE void vl_hikm_set_verbosity	(	VlHIKMTree *	f,
		int	verb
	)

Parameters:

	f	HIKM tree.
	verb	verbosity level.

void vl_hikm_train	(	VlHIKMTree *	f,
		vl_ikm_data const *	data,
		int	N
	)

Parameters:

	f	HIKM tree.
	data	Data to cluster.
	N	Number of data.

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