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A windowed correlation based feature selection method to improve time series prediction of dengue fever cases
[article]
2021
arXiv
pre-print
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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
2019
Applied Sciences
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) 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
2015
Bio-medical materials and engineering
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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
2019
Sensors
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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
2021
IEEE Access
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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]
2014
Lecture Notes in Computer Science
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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
2019
Journal of Physics, Conference Series
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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
2019
Computational and Mathematical Methods in Medicine
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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]
2014
Lecture Notes in Computer Science
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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
2021
Computational and Mathematical Methods in Medicine
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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
unpublished
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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
2010
International Journal of Computer Applications
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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
2020
IEEE Access
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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
2012
International Journal of Machine Learning and Computing
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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]
2006
Lecture Notes in Computer Science
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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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