A Survey of Neural Trees: Co-Evolving Neural Networks and Decision Trees
Neural networks (NNs) and decision trees (DTs) are both popular models of machine
learning, yet coming with mutually exclusive advantages and limitations. To bring the best of …
learning, yet coming with mutually exclusive advantages and limitations. To bring the best of …
A survey of neural trees
Neural networks (NNs) and decision trees (DTs) are both popular models of machine
learning, yet coming with mutually exclusive advantages and limitations. To bring the best of …
learning, yet coming with mutually exclusive advantages and limitations. To bring the best of …
Splitting for rare event simulation: analysis of simple cases
P Glasserman, P Heidelberger… - Proceedings of the 28th …, 1996 - dl.acm.org
An approach to rare event simulation uses the technique of splitting. The basic idea is to split
sample paths of the stochastic process into multiple copies when they approach closer to the …
sample paths of the stochastic process into multiple copies when they approach closer to the …
Flexible decision tree for data stream classification in the presence of concept change, noise and missing values
In recent years, classification learning for data streams has become an important and active
research topic. A major challenge posed by data streams is that their underlying concepts …
research topic. A major challenge posed by data streams is that their underlying concepts …
Adaptive digital makeup
A gender and skin color ethnicity based automatic digital makeup system is presented. An
automatic face makeup system which applies example based digital makeup based on skin …
automatic face makeup system which applies example based digital makeup based on skin …
Induction of fuzzy decision trees and its refinement using gradient projected-neuro-fuzzy decision tree
SJ Narayanan, RB Bhatt… - International …, 2014 - inderscienceonline.com
Fuzzy decision tree (FDT) induction is a powerful methodology to extract human
interpretable classification rules. Due to the greedy nature of FDT, there is a chance of FDT …
interpretable classification rules. Due to the greedy nature of FDT, there is a chance of FDT …
Approximating fuzzy membership functions from clustered raw data
RB Bhatt, SJ Narayanan… - 2012 Annual IEEE …, 2012 - ieeexplore.ieee.org
Clustering is the process of identifying groups of similar data fulfilling certain criteria. Fuzzy c-
means clustering algorithm generates cluster centers and degree of memberships of each …
means clustering algorithm generates cluster centers and degree of memberships of each …
[PDF][PDF] Integration of cluster centers and gaussian distributions in fuzzy c-means for the construction of trapezoidal membership function
SH Khairuddin, MH Hasan… - Mathematics and …, 2020 - researchgate.net
Abstract Fuzzy C-Means (FCM) is one of the mostly used techniques for fuzzy clustering and
proven to be robust and more efficient based on various applications. Image segmentation …
proven to be robust and more efficient based on various applications. Image segmentation …
Comparing different stopping criteria for fuzzy decision tree induction through IDFID3
M Zeinalkhani, M Eftekhari - Iranian Journal of Fuzzy Systems, 2014 - ijfs.usb.ac.ir
Fuzzy Decision Tree (FDT) classifiers combine decision trees with approximate reasoning
offered by fuzzy representation to deal with language and measurement uncertainties. When …
offered by fuzzy representation to deal with language and measurement uncertainties. When …
A Mesh-based QoS aware multicast routing protocol
D Promkotwong, O Sornil - Eighth ACIS International …, 2007 - ieeexplore.ieee.org
Due to the rising popularity of multimedia applications and potential commercial usages of
mobile ad hoc networks (MANETs), quality of service (QoS) in MANET has become …
mobile ad hoc networks (MANETs), quality of service (QoS) in MANET has become …