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A windowed correlation based feature selection method to improve time series prediction of dengue fever cases [article]

Tanvir Ferdousi, Lee W. Cohnstaedt, Caterina M. Scoglio
2021 arXiv   pre-print
A novel framework is presented for windowing incidence data and computing time-shifted correlation-based metrics to quantify feature relevance.  ...  Recurrent neural network-based prediction models achieve up to 33.6% accuracy improvement on average using the proposed method compared to using training data from the target location only.  ...  ., multivariate time series), different methods of feature selection have been used in the past including correlation-based filters [9] , [10] , Granger causality tests [11] , [12] , genetic algorithm  ... 
arXiv:2104.10289v1 fatcat:sb6trzxex5fsva5sdpbvgyvhj4

A Correlation-Change Based Feature Selection Method for IoT Equipment Anomaly Detection

Shen Su, Yanbin Sun, Xiangsong Gao, Jing Qiu, Zhihong Tian
2019 Applied Sciences  
) into our method to adapt to the online feature selection scenario.  ...  In our feature selection method, we first cluster correlated sensors together to recognize the duplicated deployed sensors according to sensor data correlations, and we monitor the data correlation changes  ...  In order to select effective features from massive high-dimensional sensor data with time-lagged correlation, this paper presents a correlation change-based feature selection method for online feature  ... 
doi:10.3390/app9030437 fatcat:krpnsdjbprebldfv42ck7dewdq

Feature gene selection method based on logistic and correlation information entropy

Jiucheng Xu, Tao Li, Lin Sun, Feng Liu, Dong-Hoon Lee, Ricardo Lagoa, Sandeep Kumar
2015 Bio-medical materials and engineering  
the feature gene selection.  ...  On the basis of this, delete redundant features by using the correlation information entropy; finally, the feature gene subset is classified by using the classifier of support vector machine (SVM).  ...  Xu et al. / Feature gene selection method based on logistic and correlation information entropy  ... 
doi:10.3233/bme-151498 pmid:26405969 fatcat:2n26pg73bfhxbk7rbpvetltsei

Selective Feature Generation Method Based on Time Domain Parameters and Correlation Coefficients for Filter-Bank-CSP BCI Systems

Yongkoo Park, Wonzoo Chung
2019 Sensors  
In contrast to existing channel selection methods based on global CSP features, the proposed algorithm utilizes the Fisher ratio of time domain parameters (TDPs) and correlation coefficients: the channel  ...  This paper presents a novel motor imagery (MI) classification algorithm using filter-bank common spatial pattern (FBCSP) features based on MI-relevant channel selection.  ...  Conclusions In this paper, we present a motor imagery (MI) classification algorithm using FBCSP features based on a MI-relevant channel selection.  ... 
doi:10.3390/s19173769 fatcat:fwhwfcld2vfmzief5ugik7gf2e

A windowed correlation-based feature selection method to improve time series prediction of dengue fever cases

Tanvir Ferdousi, Lee W. Cohnstaedt, Caterina M. Scoglio
2021 IEEE Access  
Ferdousi et al.: A windowed correlation-based feature selection method to improve time series prediction of dengue fever cases FIGURE 3 . 3 Windowing methods used for data segmentation before computing  ...  For sequential data (e.g., multivariate time series), different methods of feature selection have been used in the past including correlation-based filters [9] , [10] , Granger causality tests [11]  ... 
doi:10.1109/access.2021.3120309 fatcat:wt3k7ddcgrbjhbxhoeiurqn5qe

An Improved Correlation Method Based on Rotation Invariant Feature for Automatic Particle Selection [chapter]

Yu Chen, Fei Ren, Xiaohua Wan, Xuan Wang, Fa Zhang
2014 Lecture Notes in Computer Science  
In this paper, we presented an improved correlation method based on rotation invariant features for automatic, fast particle selection.  ...  the precision of correlation method.  ...  To overcome these problems, we propose an improved correlation method based on rotation invariant feature to implement automatic and fast selection of particles.  ... 
doi:10.1007/978-3-319-08171-7_11 fatcat:u7yxhzxwgjhrhjf3ojqev7cnuu

A Feature Selection Method based on the Pearson's Correlation and Transformed Divergence Analysis

Ying Zhang, Lin Wang, Danyang Geng, Yunfei Ai, Wei Xia, Xuejiao Bai, Shikai Sun
2019 Journal of Physics, Conference Series  
METHODS Subjects and Clinical Data This study included 143 male residents from a minorityinhabited district in Sandu county of Guizhou province.  ...  The correlations in methylation between loci were analyzed using the Pearson's test. The methylation between MEST and P16, and MEST and GNAS were positively correlated, respectively (Suppl 3).  ... 
doi:10.1088/1742-6596/1284/1/012001 fatcat:rdepvlgjgrabhbmurfvzh7brsy

Correlation-Based Ensemble Feature Selection Using Bioinspired Algorithms and Classification Using Backpropagation Neural Network

V. R. Elgin Christo, H. Khanna Nehemiah, B. Minu, A. Kannan
2019 Computational and Mathematical Methods in Medicine  
Correlation-based ensemble feature selection is performed to select the optimal features from the three feature subsets.  ...  The optimal features selected through correlation-based ensemble feature selection are used to train a gradient descendant backpropagation neural network.  ...  be selected by the correlation-based ensemble feature selector.  ... 
doi:10.1155/2019/7398307 pmid:31662787 pmcid:PMC6778924 fatcat:jbxhrmoltzaf3anetlyhwhwlpi

Tackling Ant Colony Optimization Meta-Heuristic as Search Method in Feature Subset Selection Based on Correlation or Consistency Measures [chapter]

Antonio J. Tallón-Ballesteros, José C. Riquelme
2014 Lecture Notes in Computer Science  
measures such as CFS (Correlation-based Feature Selection) and CNS (Consistency-based Feature Selection).  ...  This paper introduces the use of an ant colony optimization (ACO) algorithm, called Ant System, as a search method in two wellknown feature subset selection methods based on correlation or consistency  ...  Two of the most widespread feature subset selectors are Correlation-based Feature Selection (CFS) [8] and Consistency-based feature selection (CNS) [3] that work in combination with a search method  ... 
doi:10.1007/978-3-319-10840-7_47 fatcat:ybs3bjjkbrd5pk653wxzoft2ha

Score and Correlation Coefficient-Based Feature Selection for Predicting Heart Failure Diagnosis by Using Machine Learning Algorithms

Ebrahim Mohammed Senan, Ibrahim Abunadi, Mukti E. Jadhav, Suliman Mohamed Fati, Jose Joaquin Rieta
2021 Computational and Mathematical Methods in Medicine  
The SelectKBest function was applied with chi-squared statistical method to determine the most important features, and then feature engineering method has been applied to create new features correlated  ...  This paper proposed a machine-learning-based approach that distinguishes the most important correlated features amongst patients' electronic clinical records.  ...  The methods for selecting features by means of statistics include assessing the relationship between each feature and the target feature and selecting the input features that have the strongest correlation  ... 
doi:10.1155/2021/8500314 pmid:34966445 pmcid:PMC8712170 fatcat:7vz2dwohfzdaxifeoqifwd4byy

A stratified sampling technique based on correlation feature selection method for heart disease risk prediction system

Lalita Sharma, Vineet Khanna
unpublished
The original dataset is given to the filter Correlation based feature selection (CFS) system. The output of the system will be the efficiently achieved without stratified sampling.  ...  In this paper a stratified approach named Correlation Feature Selection Stratified Sampling (CFS-SS) has been introduced.  ...  CFS-SS is a feature selection method based on CFS. In CFS the features are selected only by calculating the correlation between features -classes and features-features.  ... 
fatcat:y7bxfbf7n5crtapsc5no46eaoq

Bi-level dimensionality reduction methods using feature selection and feature extraction

Mr. Veerabhadrappa, Lalitha Rangarajan
2010 International Journal of Computer Applications  
reduction techniques (feature selection based on Mutual correlation, PCA and LPP).  ...  In the two approaches proposed, in level 1 of dimensionality reduction, feature are selected based on mutual correlation and in level 2 selected features are used to extract features using PCA or LPP.  ...  Comparative analysis is carried out with mutual correlation based feature selection, PCA, LPP and the proposed two methods: mutual correlation based feature selection with PCA and mutual correlation based  ... 
doi:10.5120/800-1137 fatcat:wecv6b74vjgjdfumxzc7i2cixm

Comprehensive Criteria-Based Generalized Steganalysis Feature Selection Method

Yihao Wang, Yuanyuan Ma, Ruixia Jin, Pei Liu, Ning Ruan
2020 IEEE Access  
based on CGSM method after selection of CC-JRM steganalysis feature.  ...  This steganalysis feature selection method is based on the relationship between the difference function and Pearson correlation coefficient.  ... 
doi:10.1109/access.2020.3018709 fatcat:t7lgcqx5lzexbc2lkhdca5mrom

Correlation-based Feature Ordering for Classification based on Neural Incremental Attribute Learning

Ting Wang, Sheng-Uei Guan, Fei Liu
2012 International Journal of Machine Learning and Computing  
This paper presents a new method for feature ordering calculation which is based on correlations between input features and outputs.  ...  Experimental results confirm that correlation-based feature ordering can produce better classification results than contribution-based approaches, feature orderings with theoriginal sequence sorted in  ...  Similar to correlation-based feature selection, it is obvious that the greater the correlation index in (1) , the earlier the feature should be trained. IV.  ... 
doi:10.7763/ijmlc.2012.v2.242 fatcat:qxivv7rmvzg4vbcezr5zk2a5se

Feature Selection Based on Mutual Correlation [chapter]

Michal Haindl, Petr Somol, Dimitrios Ververidis, Constantine Kotropoulos
2006 Lecture Notes in Computer Science  
A novel filter feature selection method based on mutual correlation is proposed.  ...  Feature selection is a critical procedure in many pattern recognition applications. There are two distinct mechanisms for feature selection namely the wrapper methods and the filter methods.  ...  proposed correlation based feature selection algorithm can be summarized as follows.  ... 
doi:10.1007/11892755_59 fatcat:ide7t6xvvjfd3e752rtibug4he
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