CF-Tree representation. More...
Public Member Functions | |
def | root (self) |
def | leafes (self) |
def | amount_nodes (self) |
def | amount_entries (self) |
def | height (self) |
def | branch_factor (self) |
def | threshold (self) |
def | max_entries (self) |
def | type_measurement (self) |
def | __init__ (self, branch_factor, max_entries, threshold, type_measurement=measurement_type.CENTROID_EUCLIDEAN_DISTANCE) |
Create CF-tree. More... | |
def | get_level_nodes (self, level) |
Traverses CF-tree to obtain nodes at the specified level. More... | |
def | insert_cluster (self, cluster) |
Insert cluster that is represented as list of points where each point is represented by list of coordinates. More... | |
def | insert (self, entry) |
Insert clustering feature to the tree. More... | |
def | find_nearest_leaf (self, entry, search_node=None) |
Search nearest leaf to the specified clustering feature. More... | |
def | show_feature_destibution (self, data=None) |
Shows feature distribution. More... | |
CF-Tree representation.
A CF-tree is a height-balanced tree with two parameters: branching factor and threshold.
def pyclustering.container.cftree.cftree.__init__ | ( | self, | |
branch_factor, | |||
max_entries, | |||
threshold, | |||
type_measurement = measurement_type.CENTROID_EUCLIDEAN_DISTANCE |
|||
) |
Create CF-tree.
[in] | branch_factor | (uint): Maximum number of children for non-leaf nodes. |
[in] | max_entries | (uint): Maximum number of entries for leaf nodes. |
[in] | threshold | (double): Maximum diameter of feature clustering for each leaf node. |
[in] | type_measurement | (measurement_type): Measurement type that is used for calculation distance metrics. |
def pyclustering.container.cftree.cftree.amount_entries | ( | self | ) |
def pyclustering.container.cftree.cftree.amount_nodes | ( | self | ) |
def pyclustering.container.cftree.cftree.branch_factor | ( | self | ) |
def pyclustering.container.cftree.cftree.find_nearest_leaf | ( | self, | |
entry, | |||
search_node = None |
|||
) |
Search nearest leaf to the specified clustering feature.
[in] | entry | (cfentry): Clustering feature. |
[in] | search_node | (cfnode): Node from that searching should be started, if None then search process will be started for the root. |
Definition at line 953 of file cftree.py.
Referenced by pyclustering.container.cftree.cftree.find_nearest_leaf().
def pyclustering.container.cftree.cftree.get_level_nodes | ( | self, | |
level | |||
) |
Traverses CF-tree to obtain nodes at the specified level.
[in] | level | (uint): CF-tree level from that nodes should be returned. |
Definition at line 875 of file cftree.py.
Referenced by pyclustering.container.cftree.cftree.show_feature_destibution().
def pyclustering.container.cftree.cftree.height | ( | self | ) |
Definition at line 800 of file cftree.py.
Referenced by pyclustering.container.cftree.cftree.show_feature_destibution().
def pyclustering.container.cftree.cftree.insert | ( | self, | |
entry | |||
) |
Insert clustering feature to the tree.
[in] | entry | (cfentry): Clustering feature that should be inserted. |
Definition at line 927 of file cftree.py.
Referenced by pyclustering.container.kdtree.kdtree.find_minimal_node(), and pyclustering.container.cftree.cftree.insert_cluster().
def pyclustering.container.cftree.cftree.insert_cluster | ( | self, | |
cluster | |||
) |
Insert cluster that is represented as list of points where each point is represented by list of coordinates.
Clustering feature is created for that cluster and inserted to the tree.
[in] | cluster | (list): Cluster that is represented by list of points that should be inserted to the tree. |
def pyclustering.container.cftree.cftree.leafes | ( | self | ) |
def pyclustering.container.cftree.cftree.max_entries | ( | self | ) |
def pyclustering.container.cftree.cftree.root | ( | self | ) |
def pyclustering.container.cftree.cftree.show_feature_destibution | ( | self, | |
data = None |
|||
) |
def pyclustering.container.cftree.cftree.threshold | ( | self | ) |
def pyclustering.container.cftree.cftree.type_measurement | ( | self | ) |