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Ensembles of Nested Dichotomies with Multiple Subset Evaluation [article]

Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes
2018 arXiv   pre-print
A system of nested dichotomies is a method of decomposing a multi-class problem into a collection of binary problems.  ...  We provide a theoretical expectation for performance improvements, as well as empirical results showing that our method improves the root mean squared error of nested dichotomies, regardless of whether  ...  Acknowledgements This research was supported by the Marsden Fund Council from Government funding, administered by the Royal Society of New Zealand.  ... 
arXiv:1809.02740v2 fatcat:a724dtb4rrhlzp77dlzp7nxcdm

Ensembles of Nested Dichotomies with Multiple Subset Evaluation [chapter]

Tim Leathart, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes
2019 Lecture Notes in Computer Science  
A system of nested dichotomies (NDs) is a method of decomposing a multiclass problem into a collection of binary problems.  ...  as an individual model or in an ensemble setting.  ...  The use of ensembles of nested dichotomies (NDs) is one such method for decomposing a multiclass problem into several binary problems.  ... 
doi:10.1007/978-3-030-16148-4_7 fatcat:5ywneyi3i5d4hjkywlahjkr34i

ENSEMBLE META CLASSIFIER WITH SAMPLING AND FEATURE SELECTION FOR DATA WITH IMBALANCE MULTICLASS PROBLEM

Mohd Shamrie Sainin, Rayner Alfred, Faudziah Ahmad
2021 Journal of Information and Communication Technology  
In this paper, an investigation was carried out on the design of the meta classifier ensemble with sampling and feature selection for multiclass imbalanced data.  ...  classifier model; and 3 ) to evaluate t he performance of the ensemble classifier.  ...  Recent studies using END include hydraulic brake health monitoring (Jegadeeshwaran & Sugumaran, 2015) , adaptive nested dichotomies (Leathart et al., 2016) , and evolving nested dichotomies classifier  ... 
doi:10.32890/jict2021.20.2.1 fatcat:tmphsywxxjd6hcq7nwxeezkjea

Ensemble of CNN classifiers using Sugeno Fuzzy Integral Technique for Cervical Cytology Image Classification [article]

Rohit Kundu, Hritam Basak, Akhil Koilada, Soham Chattopadhyay, Sukanta Chakraborty, Nibaran Das
2021 arXiv   pre-print
Ensemble Learning is a popular approach for image classification, but simplistic approaches that leverage pre-determined weights to classifiers fail to perform satisfactorily.  ...  The main concern in developing an automatic detection tool for biomedical image classification is the low availability of publicly accessible data.  ...  Hence, we further plan to implement some evolutionary meta-heuristic optimization algorithm for the selection of the fuzzy measures of the classifiers that might further improve the overall classification  ... 
arXiv:2108.09460v1 fatcat:oxx3qim3sjg5ro42x42od5pl6e

Bayesian phylogeny analysis of vertebrate serpins illustrates evolutionary conservation of the intron and indels based six groups classification system from lampreys for ∼500 MY

Abhishek Kumar
2015 PeerJ  
for ∼500 MY.  ...  This method supports the intron and indel based vertebrate classification and proves that serpins have been maintained from lampreys to humans for about 500 MY.  ...  ACKNOWLEDGEMENTS I thank Chitra Rajakuberan for editing the final version of this manuscript. ADDITIONAL INFORMATION AND DECLARATIONS Funding The author received no funding for this article.  ... 
doi:10.7717/peerj.1026 pmid:26157611 pmcid:PMC4476131 fatcat:txssaxwlenhyfc2s4h6ipnuxse

Studi Literatur Human Activity Recognition (HAR) Menggunakan Sensor Inersia

Humaira Nur Pradani, Faizal Mahananto
2021 Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)  
Inertial sensor data processing for HAR requires a series of processes and a variety of techniques.  ...  selection methods, classification models, training scenarios, model performance, and research challenges in this topic.  ...  Akurasi tertinggi pada jenis klasifikasi ini terdapat pada angka 98,74% dengan menggunakan algoritma Ensemble of nested dichotomis (END).  ... 
doi:10.29207/resti.v5i6.3665 fatcat:q54mbcydp5curd3aadtypcrpje

Stylistic and lexical co-training for web block classification

Chee How Lee, Min-Yen Kan, Sandra Lai
2004 Proceedings of the 6th annual ACM international workshop on Web information and data management - WIDM '04  
We introduce PARCELS, an open-source, co-trained approach that performs classification based on separate stylistic and lexical views of the web page.  ...  Unlike previous work, PARCELS performs classification on fine-grained blocks.  ...  Boostexter is an ensemble learning method which combines a set of weak classifiers to determine an input vector's classification.  ... 
doi:10.1145/1031453.1031478 dblp:conf/widm/LeeKL04 fatcat:vhxkxpl2yfc5liwdtjfub2hfem

Detection of Cyberattacks Traces in IoT Data

Vibekananda Dutta, Michał Choraś, Marek Pawlicki, Rafał Kozik
2020 Journal of universal computer science (Online)  
The DAE is employed for dimensionality reduction and a host of ML methods, including Deep Neural Networks and Long Short-Term Memory to classify the outputs of into normal/malicious.  ...  Furthermore, the results of the analysis in terms of evaluation matrices are discussed.  ...  In the preliminary stage, the authors employed a balanced nested dichotomy. This is followed by a random forest classifier.  ... 
doi:10.3897/jucs.2020.075 fatcat:5jh3ruseqzd3ljl7mmzt4xt7nu

Nearshore Lagrangian Connectivity: Submesoscale Influence and Resolution Sensitivity

Daniel P. Dauhajre, James C. McWilliams
2019 Journal of Geophysical Research - Oceans  
Realistic simulation of nearshore (from the shoreline to approximately 10-km offshore) Lagrangian material transport is required for physical, biological, and ecological investigations of the coastal ocean  ...  Recently, high-resolution simulations of the coastal ocean have revealed a shelf populated with small-scale, rapidly evolving currents that arise at resolutions ⪅100 m.  ...  We thank Jeroen Molemaker for discussion of the offline Lagrangian model, Delphine Hypolite for constructive comments on earlier versions of the manuscript, and Faycal Kessouri for generation of the R1km  ... 
doi:10.1029/2019jc014943 fatcat:knzvizdunfc2rhsnvgbvy2e6aa

A Deep Learning Approach for Network Intrusion Detection System

Ahmad Javaid, Quamar Niyaz, Weiqing Sun, Mansoor Alam
2016 Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)  
We present the performance of our approach and compare it with a few previous work. Compared metrics include accuracy, precision, recall, and f-measure values.  ...  We propose a deep learning based approach for developing such an efficient and flexible NIDS.  ...  This work was further extended to use Ensembles of Balanced Nested Dichotomies (END) at the first level and Random Forest at the second level [10] .  ... 
doi:10.4108/eai.3-12-2015.2262516 dblp:journals/sesa/JavaidNSA16 fatcat:v5mkb4ttjrbehme6s6dajwsi4u

Perisomatic Inhibition

Tamás F. Freund, István Katona
2007 Neuron  
The well-balanced cooperation of the two inhibitory systems is required for the normal network operations underlying the cognitive functions of the cerebral cortex.  ...  Recent evidence supports the hypothesis of a functional dichotomy of perisomatic inhibition in the cerebral cortex: the parvalbumin-and cholecystokinin-containing basket cells that are specialized to control  ...  I.K. is a grantee of the Já nos Bolyai scholarship.  ... 
doi:10.1016/j.neuron.2007.09.012 pmid:17920013 fatcat:awzhd6ycrnepjfskltj2roi5du

Classifier Chains: A Review and Perspectives

Jesse Read, Bernhard Pfahringer, Geoffrey Holmes, Eibe Frank
2021 The Journal of Artificial Intelligence Research  
provided in the literature, as well as perspectives for this approach in the domain of multi-label classification in the future.  ...  We conclude positively, with a number of recommendations for researchers and practitioners, as well as outlining key issues for future research.  ...  Thanks also to all five anonymous reviewers, each of whom provided important discussion and suggestions, and pointed out relevant material and references, which contributed towards the development of this  ... 
doi:10.1613/jair.1.12376 fatcat:5mlsxktkend4bhssnolkmp5y6a

MMPBSA Decomposition of the Binding Energy throughout a Molecular Dynamics Simulation of Amyloid-Beta (Aß10−35) Aggregation

Josep M. Campanera, Ramon Pouplana
2010 Molecules  
The process has been characterized by means of the evolution of the decomposition of the binding free energy, which provides an energetic profile of the interaction.  ...  However, a detailed knowledge of the structure of at the atomic level has not been achieved yet due to limitations of current experimental techniques.  ...  Secondly a final set of MD simulations at NPT ensemble at 1 bar during 6 ns for each of the 26 final structures obtained in the previous step was carried out.  ... 
doi:10.3390/molecules15042730 pmid:20428075 pmcid:PMC6257327 fatcat:mx6sahenvrhadbxk2yzcqw5ceq

Global precipitation measurement: Methods, datasets and applications

Francisco J. Tapiador, F.J. Turk, Walt Petersen, Arthur Y. Hou, Eduardo García-Ortega, Luiz A.T. Machado, Carlos F. Angelis, Paola Salio, Chris Kidd, George J. Huffman, Manuel de Castro
2012 Atmospheric research  
First, the methods for measuring, estimating, and modeling precipitation are discussed. Then, the most relevant datasets gathering precipitation information from those three sources are presented.  ...  The third part of the paper illustrates a number of the many applications of those measurements and databases.  ...  ENSEMBLES RCMs are nested on ERA40 whereas PRUDENCE models are nested on a GCM. Units are mm/season. Table A.5 lists reanalysis databases.  ... 
doi:10.1016/j.atmosres.2011.10.021 fatcat:kgdxlmhvyrgvxhdmmaccvpp4ce

Personality Prediction from Social Networks text using Machine Learning

2019 International journal of recent technology and engineering  
We also prepared a Comparison chart of existing techniques for personality prediction on the basis of relevant parameters.  ...  Personality prediction has been an important research topic for describing user profiles and person not only in psychology but also in computer science.  ...  For the characteristics of Myers-Briggs, the forecast precision for the dichotomy of sensing-intuition is constantly higher, followed by the dichotomy of introversion-extroversion.  ... 
doi:10.35940/ijrte.d7146.118419 fatcat:6yubadcstrdkrpmtqn4qrsjg24
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