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Speed up kernel discriminant analysis

Deng Cai, Xiaofei He, Jiawei Han
2010 The VLDB journal  
In this paper, we present a new algorithm for kernel discriminant analysis, called Spectral Regression Kernel Discriminant Analysis (SRKDA).  ...  LDA can be performed either in the original input space or in the reproducing kernel Hilbert space (RKHS) into which data points are mapped, which leads to kernel discriminant analysis (KDA).  ...  Our analysis essentially follows our previous idea for speeding up LDA [6] .  ... 
doi:10.1007/s00778-010-0189-3 fatcat:it4o4ogxlrevjno7mkan4jmwrm

Speed-up and Multi-view Extensions to Subclass Discriminant Analysis

Kateryna Chumachenko, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
2020 Pattern Recognition  
In this paper, we propose a speed-up approach for subclass discriminant analysis and formulate a novel efficient multi-view solution to it.  ...  Furthermore, we formulate a novel criterion for multi-view subclass discriminant analysis and show that an efficient solution to it can be obtained in a similar manner to the single-view case.  ...  In this paper, we propose a speed-up approach for SDA and its kernelized form, i.e., Kernel Subclass Discriminant Analysis (KSDA) [16] .  ... 
doi:10.1016/j.patcog.2020.107660 fatcat:gldnc23ocrbe7jzadm2qig2ml4

Direct kernel biased discriminant analysis: a new content-based image retrieval relevance feedback algorithm

Dacheng Tao, Xiaoou Tang, Xuelong Li, Yong Rui
2006 IEEE transactions on multimedia  
To explore solutions to this issue, this paper proposes a direct kernel BDA (DKBDA), which is less sensitive to SSS. An incremental DKBDA (IDKBDA) is also developed to speed up the analysis.  ...  Index Terms-Biased discriminant analysis (BDA), contentbased image retrieval (CBIR), direct kernel biased discriminant analysis (DKBDA), incremental direct kernel biased discriminant analysis (IDKBDA),  ...  Incremental DKBDA is also developed to speed up the DKBDA.  ... 
doi:10.1109/tmm.2005.861375 fatcat:nhyax6v7irbyrijj7is5xejnhi

Speed-up and multi-view extensions to Subclass Discriminant Analysis [article]

Kateryna Chumachenko, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
2019 arXiv   pre-print
In this paper, we propose a speed-up approach for subclass discriminant analysis and formulate a novel efficient multi-view solution to it.  ...  Furthermore, we formulate a novel criterion for multi-view subclass discriminant analysis and show that an efficient solution for it can be obtained in a similar to the single-view manner.  ...  In this paper, we propose a speed-up approach for SDA and its kernelized form, i.e., Kernel Subclass Discriminant Analysis (KSDA) [16] .  ... 
arXiv:1905.00794v1 fatcat:iwwj2t2w3jccfjdfxn2g52gzra

Incremental Fast Subclass Discriminant Analysis [article]

Kateryna Chumachenko, Jenni Raitoharju, Moncef Gabbouj, Alexandros Iosifidis
2020 arXiv   pre-print
This paper proposes an incremental solution to Fast Subclass Discriminant Analysis (fastSDA). We present an exact and an approximate linear solution, along with an approximate kernelized variant.  ...  The speed-up given by this solution is two-fold: first, the speed-up is achieved as the inverse calculation is omitted; second, the resulting method does not require recalculation of the full kernel matrix  ...  These methods are referred to as fast Subclass Discriminant Analysis (fastSDA) and fast Kernel Subclass Discriminant Analysis (fastKSDA) for the linear and non-linear cases, respectively.  ... 
arXiv:2002.04348v1 fatcat:a5fbcg4idrghlp2qj3y4w5ttjm

Precise and stable edge orientation signaling by human first-order tactile neurons [article]

Vaishnavi Sukumar, Roland S Johansson, J. Andrew Pruszynski
2022 bioRxiv   pre-print
Represented in the spatial domain, the sequential structure was strikingly invariant across scanning speeds, especially those naturally used in tactile spatial discrimination tasks.  ...  This speed invariance suggests that neurons' responses are structured via sequential stimulation of their subfields.  ...  Regarding the speed effect, for both neuron types, the discrimination accuracy was fairly uniform for speeds up to 45 mm/s, after which it gradually decreased with increasing speed.  ... 
doi:10.1101/2022.06.01.494420 fatcat:7qs5y2v5vrcabcbbdfsba4elw4

Identification of Damaged Wheat Kernels and Cracked-Shell Hazelnuts with Impact Acoustics Time-Frequency Patterns

N. F. Ince, I. Onaran, T. Pearson, A. H. Tewfik, A. E. Cetin, H. Kalkan, Y. Yardimci
2008 American Society of Agricultural and Biological Engineers. Transactions  
These signals were segmented with a flexible local discriminant bases (F-LDB) procedure in the time-frequency plane to extract discriminative patterns between damaged and undamaged food kernels.  ...  Discriminant features are extracted from the adaptively segmented acoustic signal, sorted according to a Fisher class separability criterion, post-processed by principal component analysis, and fed to  ...  Finally, linear discriminant analysis is used to identify damaged food kernel acoustics.  ... 
doi:10.13031/2013.25226 fatcat:553qxkarnngcnkehpuqi43jlie

Benchmarking Machine Learning Approaches to Evaluate the Cultivar Differentiation of Plum (Prunus domestica L.) Kernels

Ewa Ropelewska, Xiang Cai, Zhan Zhang, Kadir Sabanci, Muhammet Fatih Aslan
2022 Agriculture  
Emper', 'Kalipso', and 'Polinka', and discriminant analysis using machine learning algorithms to classify plum kernel cultivars based on selected textures with the highest discriminative power.  ...  The promising procedure for distinguishing plum kernel cultivars used in this study comprised two stages: image analysis to compute the texture parameters of plum kernels belonging to three cultivars '  ...  Machine learning proved to be useful to speed up the evaluation of germination of seeds belonging to different cultivars and to achieve higher results and performance than manual and conventional methods  ... 
doi:10.3390/agriculture12020285 fatcat:6liytiln7rhijl2eadvyuqdm6e

Discrimination of Transgenic Maize Kernel Using NIR Hyperspectral Imaging and Multivariate Data Analysis

Xuping Feng, Yiying Zhao, Chu Zhang, Peng Cheng, Yong He
2017 Sensors  
model based on these important wavelengths to simplify the prediction model and to speed up the operation; and (4) to visualize the number and locations of GM maize kernel by developing imaging processing  ...  the discriminant models to class the GM maize kernels from their contrast.  ...  Variable selection was carried out using CARS election-based techniques to reduce the effect of non-related variables and speed up the classification.  ... 
doi:10.3390/s17081894 pmid:28817075 pmcid:PMC5580036 fatcat:4dojxqb6tbh7xcyfx7yqite3qe

Evaluation of supervised classification algorithms for human activity recognition with inertial sensors

Tahmina Zebin, Patricia J. Scully, Krikor B. Ozanyan
2017 2017 IEEE SENSORS  
Our results show that Support Vector Machines with quadratic kernel classifier (accuracy: 93.5%) and Ensemble classifier with bagging and boosting (accuracy: 94.6%) outperforms other known activity classification  ...  Linear and Quadratic Discriminant analysis was not found to be suitable for classifying activity from the inertial sensor data because the covariance of the predictors did not produce sufficient discrimination  ...  Features were extracted from the raw acceleration and gyroscopic data collected from these sensors, and then algorithms such as Decision Tree, Linear and Quadratic Discriminant Analysis, Support Vector  ... 
doi:10.1109/icsens.2017.8234222 fatcat:ec3fdyhi2zdzfi5lllc2u4y4s4

SDRNF: generating scalable and discriminative random nonlinear features from data

Haoda Chu, Kaizhu Huang, Rui Zhang, Amir Hussian
2016 Big Data Analytics  
Compared with exact kernel methods, this family of approaches is capable of speeding up the training process dramatically, while maintaining acceptable the classification accuracy.  ...  Real world data analysis problems often require nonlinear methods to get successful prediction. Kernel methods, e.g.  ...  To speed up the process of kernel methods, one recent active research focused on using randomized tricks to build scalable kernel approximation [7] [8] [9] [10] .  ... 
doi:10.1186/s41044-016-0015-z fatcat:ey6vzhrvlvg25mn4zvlxdcynhq

Direct calculation of out-of-sample predictions in multi-class kernel FDA

Matthias Treder
2019 The European Symposium on Artificial Neural Networks  
After a two-class kernel Fisher Discriminant Analysis (KFDA) has been trained on the full dataset, matrix inverse updates allow for the direct calculation of out-of-sample predictions for different test  ...  Crossvalidation was up to 1000x faster and permutation testing was up to 10,000x faster. Complexity.  ...  out-of-sample discriminant scores.  ... 
dblp:conf/esann/Treder19 fatcat:ox6ljpt23vayxni226uzz6ucbm

A Nonlinearized Discriminant Analysis and Its Application to Speech Impediment Therapy [chapter]

András Kocsor, László Tóth, Dénes Paczolay
2001 Lecture Notes in Computer Science  
kernel-idea'.  ...  In particular, we focus on how efficiently discriminant analysis can reduce the number of features and increase classification performance.  ...  1 In [4] this method bears the name "Kernel Fisher Discriminant Analysis".  ... 
doi:10.1007/3-540-44805-5_33 fatcat:nr2h6sses5bufn3pc5bgdkovay


T. C. Pearson, D. T. Wicklow, E. B. Maghirang, F. Xie, F. E. Dowell
2001 Transactions of the ASAE  
The two-feature discriminant analysis oftransmittance data gave the best results.  ...  Spectra were analyzed using discriminant analysis and partial least squares regression.  ...  CLASSIFICATION BY DISCRIMINANT ANALYSIS Classification results using discriminant analysis are shown in table 2.  ... 
doi:10.13031/2013.6418 fatcat:bka3tzk3ufb2rauk2mujlst2ea

Matching Pursuit Kernel Fisher Discriminant Analysis

Tom Diethe, Zakria Hussain, David R. Hardoon, John Shawe-Taylor
2009 Journal of machine learning research  
We call this algorithm Matching Pursuit Kernel Fisher Discriminant Analysis (MPKFDA).  ...  We derive a novel sparse version of Kernel Fisher Discriminant Analysis (KFDA) using an approach based on Matching Pursuit (MP).  ...  Another issue of speeding up the algorithm may be to consider approximating ρ.  ... 
dblp:journals/jmlr/DietheHHS09 fatcat:w2mtdoh5krazlpeoqdi3kxvip4
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