frlearn.neighbours.classifiers.FRNN

class frlearn.neighbours.classifiers.FRNN(*, upper_weights: frlearn.utils.owa_operators.OWAOperator = <frlearn.utils.owa_operators.additive object>, upper_k: int = 20, lower_weights: frlearn.utils.owa_operators.OWAOperator = <frlearn.utils.owa_operators.additive object>, lower_k: int = 20, nn_search: frlearn.neighbours.neighbour_search.NNSearch = <frlearn.neighbours.neighbour_search.KDTree object>)[source]

Implementation of Fuzzy Rough Nearest Neighbour (FRNN) classification (FRNN).

Parameters
upper_weightsOWAOperator, default=additive()

OWA weights to use in calculation of upper approximation of decision classes.

upper_kint, default = 20

Effective length of upper weights vector (number of nearest neighbours to consider).

lower_weightsOWAOperator, default=additive()

OWA weights to use in calculation of lower approximation of decision classes.

lower_kint, default = 20

Effective length of lower weights vector (number of nearest neighbours to consider).

nn_searchNNSearch, default=KDTree()

Nearest neighbour search algorithm to use.

Notes

With strict upper_weights and lower_weights, this is FRNN classification as presented in [R1fba870e1728-1]. The use of OWA operators for the calculation of fuzzy rough sets was proposed in [R1fba870e1728-2], and OWA operators were first explicitly combined with FRNN in [R1fba870e1728-3].

References

R1fba870e1728-1

Jensen R, Cornelis C (2008). A New Approach to Fuzzy-Rough Nearest Neighbour Classification. In: Chan CC, Grzymala-Busse JW, Ziarko WP (eds). Rough Sets and Current Trends in Computing. RSCTC 2008. Lecture Notes in Computer Science, vol 5306. Springer, Berlin, Heidelberg. doi: 10.1007/978-3-540-88425-5_32

R1fba870e1728-2

Cornelis C, Verbiest N, Jensen R (2010). Ordered Weighted Average Based Fuzzy Rough Sets. In: Yu J, Greco S, Lingras P, Wang G, Skowron A (eds). Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science, vol 6401. Springer, Berlin, Heidelberg. doi: 10.1007/978-3-642-16248-0_16

R1fba870e1728-3

E. Ramentol et al., IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification. IEEE Transactions on Fuzzy Systems, vol 23, no 5, pp 1622-1637, Oct 2015. doi: 10.1109/TFUZZ.2014.2371472

__init__(self, *, upper_weights: 'OWAOperator' = <frlearn.utils.owa_operators.additive object at 0x7f8b1a501ed0>, upper_k: 'int' = 20, lower_weights: 'OWAOperator' = <frlearn.utils.owa_operators.additive object at 0x7f8b1a501fd0>, lower_k: 'int' = 20, nn_search: 'NNSearch' = <frlearn.neighbours.neighbour_search.KDTree object at 0x7f8b1a5085d0>)[source]

Initialize self. See help(type(self)) for accurate signature.

class Model(classifier, X, y)