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Stacking Class Probabilities Obtained from View-Based Cluster Ensembles
[chapter]
2010
Lecture Notes in Computer Science
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The domain knowledge, for example, can be used to group some of the features together, which are also known as "views". ...
In this work, we demonstrate that even very simple features such as class-distributions within clusters of each view can serve as such valuable features. ...
presented to Fuzzy ARTMAP, where C is the number of classes and V is the number of views. ...
doi:10.1007/978-3-642-13208-7_50
fatcat:hwiz2qiyrrah5abggo6a2t4jsm
Incremental Learning for Classification of Protein Sequences
2007
Neural Networks (IJCNN), International Joint Conference on
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The use of an evolutionary strategy in the selection and combination of individual classifiers into an ensemble system, coupled with the incremental learning ability of the fuzzy ARTMAP is proven to be ...
The fuzzy ARTMAP is found to be comparable to many of the widespread machine learning systems. ...
This paper introduces the use of a classification system based upon an evolutionary strategy, incremental learning and the Fuzzy ARTMAP to realise a protein classification system for the GPCR protein superfamily ...
doi:10.1109/ijcnn.2007.4370924
dblp:conf/ijcnn/MohamedRM07
fatcat:qcwqdauubvgzbo7c6mnxh7ug7q
An adaptive strategy for the classification of g-protein coupled receptors
2007
SAIEE Africa Research Journal
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The fuzzy ARTMAP is found to be comparable to many or the widespread machine learning systems. ...
The algorithm presentcd is tested using data from the G-Coupled Protein Receptors Database and shows good accuracy of 83%. ...
This paper introduces the use of a classification system based upon an evolutionary strategy, incremental learning and the Fuzzy ARTMAP to realise a protein classification system for the GPCR protein super-family ...
doi:10.23919/saiee.2007.9488130
fatcat:kcn7lxjblbhwbjga4mi7mmmuxy
Automation of DNA Finger Printing for Precise Pattern Identification using Neural fuzzy Mapping approach
2011
International Journal of Computer Applications
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The perfect blend made of bioinformatics, neural networks and fuzzy logic results in efficient algorithms of pattern analysis techniques that induce automation which is inevitable in DNA profiling that ...
The Neural networks suitable particularly for pattern classification problems in realistic environment is simplified fuzzy ARTMAP [1] [4] [5] , it is a vast simplification of fuzzy ARTMAP which has ...
The FASTA format may be used to represent either single sequences or many sequences in a single file. A series of single sequences, concatenated, constitute a multi sequence file. ...
doi:10.5120/1761-2411
fatcat:v3rpztzcmzanbier6laac4fbi4
A Wide Scale Classification of Class Imbalance Problem and its Solutions: A Systematic Literature Review
2019
Journal of Computer Science
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The imbalanced dataset consists of a majority class and a minority class, where the majority class takes the lead over the minority class. ...
To overcome this problem (or improving accuracy of deision/prediction-making process), data mining and machine learning researchers have addressed the problem of imbalanced data using datalevel, algorithmic ...
with SOM
DT
AUC
UCI repository
Hinojosa et al. (2015)
SMOTE + Tomek link
Iterative fuzzy classification
AUC
KEEL repository
Rules Learning, Multi-
Objective EA
Hosseinzadeh and
Fuzzy-based ...
doi:10.3844/jcssp.2019.886.929
fatcat:cg3x36g4rzhybi7xzca6rfyaqi
The use of computational intelligence in intrusion detection systems: A review
2010
Applied Soft Computing
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The scope of this review will be on core methods of CI, including artificial neural networks, fuzzy systems, evolutionary computation, artificial immune systems, swarm intelligence, and soft computing. ...
The research contributions in each field are systematically summarized and compared, allowing us to clearly define existing research challenges, and to highlight promising new research directions. ...
Fig. 23 . 23 A multi-class classification algorithm based on multiple ant colonies [142] . ...
doi:10.1016/j.asoc.2009.06.019
fatcat:5ntbfbejrveyzhmmelfh34qkiy
Selective negative correlation learning approach to incremental learning
2009
Neurocomputing
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Further, comparisons between SNCL and other existing incremental learning algorithms, such Learn þ þ and ARTMAP, are also presented. ...
For example, Carpenter et al. proposed the adaptive resonance theory modules map (ARTMAP) [3] and fuzzy ARTMAP [4] in 1991 and 1992, respectively. ...
The SCR data set was generated on the basis of protein sequences obtained from MegaMotifBase database [24] . The task is to identify structurally conserved residues on the sequences. ...
doi:10.1016/j.neucom.2008.09.022
fatcat:vtxfgoqhnfhuxfm65jyr5g2go4
An incremental approach to automated protein localisation
2008
BMC Bioinformatics
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To our knowledge, a combination of both approaches -i.e. a technique, which enables supervised learning using a known set of protein locations and is able to identify and incorporate new protein locations ...
Even dynamic processes can be captured, which can barely be predicted based on amino acid sequences. ...
Here, we propose the application of an extended version of the simplified fuzzy ARTMAP (SFAM) originally introduced in [46] as a classifier. ...
doi:10.1186/1471-2105-9-445
pmid:18937856
pmcid:PMC2603336
fatcat:haqskg253vg4pobtthzq63nmxa
Improving the Security of the Chien-Jan Protocol for Large Mobile Networks
2007
Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2007)
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L1-norm with Image Watermarking on SVD Domain Amnach Khawne, Orachat Chitsobhuk, and Toshiyuki Nakamiya IIHMSP-2007-IS16-001 Blind Multi-Class Steganalysis System Using Wavelet Statistics Antonio Savoldi ...
Rizon, and Sazali Yaacob IIHMSP-2007-IS02-003 Keystroke Patterns Classification using the ARTMAP-FD Neural Network Chen Change Loy, Weng Kin Lai, and Chee Peng Lim IIHMSP-2007-IS02-004 A Mutation-Based ...
doi:10.1109/iihmsp.2007.4457537
dblp:conf/iih-msp/ChanW07
fatcat:jjurabaaqvem7eqbe5ewkzacfy
Program
2009
2009 International Joint Conference on Neural Networks
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Patra and Yongjin Li P249 Global Uniform Stability Analysis of Biological Networks With Different Time -Scales Under Perturbations Anke Meyer-Baese P250 Inferring Protein Interactions From Sequence Using ...
LS-SVM Mathias Adankon and Mohamed Cheriet P227 A Support Vector Hierarchical Method for Multi-class Classification and Rejection Yu-Chiang Frank Wang and David Casasent P228 Subspace Based Linear Programming ...
doi:10.1109/ijcnn.2009.5178575
fatcat:kxaceopferd23ps5uyrn3m7xjy
Artificial Neural Network in Drug Delivery and Pharmaceutical Research
2013
The Open Bioinformatics Journal
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, analytical data analysis, drug modeling, protein structure and function, dosage optimization and manufacturing, pharmacokinetics and pharmacodynamics modeling, and in vitro in vivo correlations. ...
ANNs do not require rigidly structured experimental designs and can map functions using historical or incomplete data, which makes them a powerful tool for simulation of various non-linear systems.ANNs ...
The PRED-CLASS trained using 50 protein sequences, correctly predicted 371 out of a set of 387 proteins with an accuracy of 96 percent. ...
doi:10.2174/1875036201307010049
fatcat:z2zeq4xgrfcu5iuzjxu7ji6434
Hyperparameter optimization in learning systems
2019
Journal of Membrane Computing
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The goal is to find a set of hyperparameter values which gives us the best model for our data in a reasonable amount of time. ...
We present an integrated view of methods used in hyperparameter optimization of learning systems, with an emphasis on computational complexity aspects. ...
In [5] , we optimized the hyperparameters of a class of Fuzzy ARTMAP neural networks, Fuzzy ARTMAP with Input Relevances (FAMR). ...
doi:10.1007/s41965-019-00023-0
fatcat:mlm7rpjy6fgazork6vhknqk6ta
Streaming chunk incremental learning for class-wise data stream classification with fast learning speed and low structural complexity
2019
PLoS ONE
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newly proposed method, named streaming chunk incremental learning (SCIL), increases the plasticity and the adaptabilty of the network structure according to the distribution of incoming data and their classes ...
Their experimental results showed that the Learn++ classifier outperformed fuzzy ARTMAP on four benchmarked and real-world data sets, but the classifier is sensitive to parameters of the network used. ...
One of the solutions to reduce the effect of sensitivity of the sequence is learning through a data chunk with one class at a time. ...
doi:10.1371/journal.pone.0220624
pmid:31498787
pmcid:PMC6733468
fatcat:ohohbz7twjbb3bseuxhfr5lese
A Review of the Modification Strategies of the Nature Inspired Algorithms for Feature Selection Problem
2022
Mathematics
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Hybridization is the most widely used modification technique. ...
The most widely used hybridization is the one that integrates a classifier with the NIA. ...
ACO used GA operators to update the solutions. The GPCR-PROSITE dataset and ENZYME-PROSITE challenging protein sequences data sets were used. ...
doi:10.3390/math10030464
fatcat:sjg667gilzfktokxxjwdg52jbm
Noise Benefits in Expectation-Maximization Algorithms
[article]
2014
arXiv
pre-print
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Expectation-Maximization algorithms are a class of iterative algorithms for extracting maximum likelihood estimates from corrupted or incomplete data. ...
Extensions to the ART framework include ARTMAP [44] for supervised classification learning and Fuzzy ART for fuzzy clustering [45] . ...
A similar likelihood model applies for motif identification in biopolymer sequences like proteins. Proteins just use a symbol lexicon of amino acids instead of nucleotides. ...
arXiv:1411.6622v1
fatcat:wanw4zq26fhl5jkrhy3ce2wzbq
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