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Provissional Access For Improving Classification Accuracy On Diabetes Dataset

2019 International Journal of Engineering and Advanced Technology  
Preprocessing is a data mining technique that transforms the unrefined dataset into reliable and useful data. It is used for resolving the issues and changes raw data for next level processing.  ...  Discretization is a necessary step for data preprocessing task. It reduces the large chunks of numeric values to a group of well-organized values.  ...  INTRODUCTION Knowledge discovery is a complex process that is used in data mining.  ... 
doi:10.35940/ijeat.f9389.088619 fatcat:def6ysap2bbtpkzhbxwdcbh3gy

Information Maps: A Practical Approach to Position Dependent Parameterization [article]

Benjamin wilking, Daniel Meissner, Stephan Reuter, Klaus Dietmayer
2013 arXiv   pre-print
These parameters can be obtained, among others, using experimental results or expert knowledge and are stored in 'Information Maps'.  ...  Thus, for instance, it is feasible to store arbitrary attributes of a sensor's preprocessing in an Information Map and utilize them by simply taking the map value at the current position.  ...  When using a sensor with measurements which can't be transformed into the vehicle coordinates, e.g. a camera, special a priori knowledge is needed.  ... 
arXiv:1312.3808v1 fatcat:kgnea45mtnaoppe7jjbt2eruve

scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data

Wenbin Ye, Guoli Ji, Pengchao Ye, Yuqi Long, Xuesong Xiao, Shuchao Li, Yaru Su, Xiaohui Wu
2019 BMC Genomics  
We have made scNPF an easy-to-use R package, which can be used as a versatile preprocessing plug-in for most existing scRNA-seq analysis pipelines or tools. scNPF is a universal tool for preprocessing  ...  knowledge from diverse data sources. scNPF could be used to recover gene signatures and learn cell-to-cell similarities from emerging scRNA-seq data to facilitate downstream analyses such as dimension  ...  Availability of data and materials Datasets used for the analyses in this study are summarized in Additional file 2: Table S1 .  ... 
doi:10.1186/s12864-019-5747-5 pmid:31068142 pmcid:PMC6505295 fatcat:zwt6xpuuwjgl7mrwp5fbwz4iy4

Page 1076 of Behavior Research Methods Vol. 41, Issue 4 [page]

2009 Behavior Research Methods  
This weight may be chosen on the basis of a priori knowledge— for instance, information concerning the reliability of the data—or on the basis of results from previous studies.  ...  To this end, a model se¬ lection heuristic may be used.  ... 

Performance of Different Atrial Conduction Velocity Estimation Algorithms Improves with Knowledge about the Depolarization Pattern

Claudia Nagel, Nicolas Pilia, Laura Unger, Olaf Dössel
2019 Current Directions in Biomedical Engineering  
We propose an extension to all approaches by including a distinct preprocessing step.  ...  All of them are solely based on the local activation times calculated from electroanatomical mapping data. They deliver false values for the CV if applied to regions near scars or wave collisions.  ...  This a-priori knowledge about the depolarization pattern is then included in the CV estimation routine.  ... 
doi:10.1515/cdbme-2019-0026 fatcat:3cvyuvjoovelbadtarwlfzh7xe

BCI Competition 2003—Data Set IIb: Enhancing P300 Wave Detection Using ICA-Based Subspace Projections for BCI Applications

N. Xu, X. Gao, B. Hong, X. Miao, S. Gao, F. Yang
2004 IEEE Transactions on Biomedical Engineering  
After ICA decomposition, P300-related independent components are selected according to the a priori knowledge of P300 spatio-temporal pattern, and clear P300 peak is reconstructed by back projection of  ...  RESULTS To confirm the a priori knowledge of P300 used in the section on spatial and temporal manipulation, the time and space distributions of P300 were investigated.  ...  First, we decompose the multichannel EEG data into ICs by ICA, then we make the manipulative selection of the ICs based on the a priori knowledge of P300 spatio-temporal pattern, and finally project them  ... 
doi:10.1109/tbme.2004.826699 pmid:15188880 fatcat:audyc4jckrg35bkgx2mqgz7xzy

The NeuroBayes neural network package

M. Feindt, U. Kerzel
2006 Nuclear Instruments and Methods in Physics Research Section A : Accelerators, Spectrometers, Detectors and Associated Equipment  
Detailed analysis of correlated data plays a vital role in modern analyses.  ...  The network provides numerous possibilities to automatically preprocess the input variables and uses advanced regularisation and pruning techniques to essentially eliminate the risk of overtraining.  ...  The Expertise is then used by the NeuroBayes Expert analysing the data of interest. The Bayesian Approach NeuroBayes uses Bayesian statistics to incorporate a priori knowledge.  ... 
doi:10.1016/j.nima.2005.11.166 fatcat:tdfgi2tnlfgp7d3uejocth754i

Handwritten digit recognition by neural networks with single-layer training

S. Knerr, L. Personnaz, G. Dreyfus
1992 IEEE Transactions on Neural Networks  
We present results from two different data bases: a European data base comprising 8,700 isolated digits, and a zip code data base from the U.S. Postal Service comprising 9,000 segmented digits.  ...  Provided appropriate data representations and learning rules are used, performances which are comparable to those obtained by more complex networks can be achieved.  ...  Postal Service for providing us with the OAT Handwritten Zip Code Data Base (1987). This work was supported in part by EEC BRAIN contract ST2000422.  ... 
doi:10.1109/72.165597 pmid:18276492 fatcat:nhga3vxgabcb3ir7cplgn6twjq

Clinical Knowledge Discovery in Hospital Information Systems: Two Case Studies [chapter]

Shusaku Tsumoto
2000 Lecture Notes in Computer Science  
because human beings cannot deal with such a huge amount of data.  ...  by using two medical datasets.  ...  For those steps, the indispensable attributes and the threshold for the second selection are given a priori by domain experts. Table 2 summarizes results for data cleaning.  ... 
doi:10.1007/3-540-45372-5_80 fatcat:glke4xes7jetramd72c337tmpe

Qualitative Evolution of Performance and Validity Indices for Web Usage Mining

Narendra Kumar Kachhwaha, Bhupendra K Malviya
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
Web Usage Mining relates mining techniques in log data to extract the performance of users which is used in different applications like Support to the Design, E-commerce, Modified services, prefetching  ...  Finally a glance of various applications of web usage mining is presented. Web Usage Mining has develop into a dynamic region of study in field of data mining because of its crucial values.  ...  Experiments have established that advanced data preprocessing knowledge can improve the quality of data preprocessing outcomes.In Web Usage Mining, web session clustering plays an important key role to  ... 
doi:10.23956/ijarcsse/sv7i5/0198 fatcat:d654x5uchbenbft2bp5szckbva

Support Vector Machines based on a semantic kernel for text categorization

G. Siolas, F. d'Alche-Buc
2000 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium  
We propose to solve a text categorization task using a new metric between documents, based on a priori semantic knowledge about words.  ...  Support Vector Machines provide the best accuracy on test data.  ...  following preprocessing of the data.  ... 
doi:10.1109/ijcnn.2000.861458 dblp:conf/ijcnn/Siolasd00 fatcat:t2vgrpt3xrhdppaiug56jmjali

Page 149 of American Society of Civil Engineers. Collected Journals Vol. 114, Issue 4 [page]

1988 American Society of Civil Engineers. Collected Journals  
An a priori knowledge of the coordinates of station A allows the determination of the coordinates of all the other un- known stations.  ...  Of major importance during the preprocessing stage is the detection and repair of cycle slips in the phase data (de la Fuente 1988).  ... 

A Text-Driven Aircraft Fault Diagnosis Model Based on a Word2vec and Priori-Knowledge Convolutional Neural Network

Zhenzhong Xu, Bang Chen, Shenghan Zhou, Wenbing Chang, Xinpeng Ji, Chaofan Wei, Wenkui Hou
2021 Aerospace (Basel)  
In the process of aircraft maintenance and support, a large amount of fault description text data is recorded.  ...  Validation experiments on five-year maintenance log data of a civil aircraft were carried out to successfully verify the effectiveness of the proposed model.  ...  Aircraft Fault Text Text Preprocessing Word2vec Feature Extraction Priori-Knowledge CNN Fault Diagnosis Text Data Preprocessing Text data preprocessing is quite different from structured data preprocessing  ... 
doi:10.3390/aerospace8040112 fatcat:66fqla2r4fcftay6jrfig3zcca

PREMER: Parallel Reverse Engineering of Biological Networks with Information Theory [chapter]

Alejandro F. Villaverde, Kolja Becker, Julio R. Banga
2016 Lecture Notes in Computer Science  
A preprocessing module takes care of imputing missing data and correcting outliers if needed.  ...  It recovers network topology and estimates the strength and causality of interactions using information theoretic criteria, and allowing the incorporation of prior knowledge.  ...  It also features a data preprocessing step which enables the use of datasets with missing values and/or outliers. PREMER is freely available as a Matlab/Octave toolbox.  ... 
doi:10.1007/978-3-319-45177-0_21 fatcat:w4ufb4xlljhaflem675sg6s7pe

Improving the performance of GA–ML DOA estimator with a resampling scheme

Ming-Hui Li, Yi-Long Lu
2004 Signal Processing  
methods of MUSIC or ESPRIT. where a( ) represents the a priori known L £ 1 array manifold, and the entries in the vector μ p contain the pth source's a priori unknown azimuth-elevation direction-of-arrival  ...  As the array manifold's mathematical form a(μ) is assumed as a priori known, form the MUSIC pseudospectrum scalar function: V(μ) = 1=a H (μ)E n E H n a(μ).  ... 
doi:10.1016/j.sigpro.2004.06.009 fatcat:zlbh3ckpprcgjo7nheas6bzudy
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