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Missing Data Prediction using Correlation Genetic Algorithm and SVM Approach

https://doi.org/10.14569/ijacsa.2020.0110288
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-211-89836-9_1025openalex-snapshot
Pearson correlation coefficient
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A Genetic Algorithm to Configure Support Vector Machines for Predicting Fault-Prone Components
inferredcites →https://doi.org/10.1016/j.asoc.2019.01.022openalex-snapshot
Gaussian kernels for incomplete data
inferredcites →https://doi.org/10.1016/j.neunet.2005.06.025openalex-snapshot
Handling missing values in support vector machine classifiers
inferredcites →https://doi.org/10.1109/access.2016.2606242openalex-snapshot
Temporal Dynamic Matrix Factorization for Missing Data Prediction in Large Scale Coevolving Time Series
inferredcites →https://doi.org/10.1109/access.2020.2969204openalex-snapshot
Adaptive Fuzzy Map Approach for Accruing Velocity of Big Data Relies on Fireflies Algorithm for Decentralized Decision Making
inferredcites →https://doi.org/10.1109/cist.2018.8596389openalex-snapshot
A Study of Handling Missing Data Methods for Big Data
inferredcites →https://doi.org/10.1109/csse.2008.924openalex-snapshot
Improved Kriging Interpolation Based on Support Vector Machine and Its Application in Oceanic Missing Data Recovery
inferredcites →https://doi.org/10.1109/cyberc.2016.53openalex-snapshot
A Novel Missing-Rate-Oriented Selective Algorithm for Handling Missing Data by Minimizing Imputation
inferredcites →https://doi.org/10.1109/icassp.2009.4960347openalex-snapshot
Missing data recovery via a nonparametric iterative adaptive approach
inferredcites →https://doi.org/10.1109/icsdm.2011.5969061openalex-snapshot
Genetic algorithm optimized SVM in object-based classification of quickbird imagery
inferredcites →https://doi.org/10.1109/ictis.2015.7232119openalex-snapshot
A genetic algorithm-based support vector machine for bus travel time prediction
inferredcites →https://doi.org/10.1109/ictss.2016.7792849openalex-snapshot
Missing data handling using machine learning for human activity recognition on mobile device
inferredcites →https://doi.org/10.1109/ijcnn.2006.1716515openalex-snapshot
Genetic Algorithms for Support Vector Machine Model Selection
inferredcites →https://doi.org/10.1109/inds.2014.25openalex-snapshot
Handling Missing Data Problems with Sampling Methods
inferredcites →https://doi.org/10.1109/ispacs.2014.7024450openalex-snapshot
Genetic algorithm assisted by a SVM for feature selection in gait classification
inferredcites →https://doi.org/10.1109/jbhi.2013.2288803openalex-snapshot
Tensor-Based Methods for Handling Missing Data in Quality-of-Life Questionnaires
inferredcites →https://doi.org/10.1109/jbhi.2016.2634587openalex-snapshot
Tackling Missing Data in Community Health Studies Using Additive LS-SVM Classifier
inferredcites →https://doi.org/10.1109/tcyb.2018.2872800openalex-snapshot
A Transfer-Based Additive LS-SVM Classifier for Handling Missing Data
inferredcites →https://doi.org/10.1109/tim.2014.2342431openalex-snapshot
Frequency Response Function Estimation in the Presence of Missing Output Data
inferredcites →https://doi.org/10.1109/tkde.2018.2833850openalex-snapshot
An Efficient Semi-Supervised Multi-label Classifier Capable of Handling Missing Labels
inferredcites →https://doi.org/10.1142/s1469026811003215openalex-snapshot
APPLICATION OF GENETIC ALGORITHM-SUPPORT VECTOR MACHINE (GA-SVM) FOR DAMAGE IDENTIFICATION OF BRIDGE
inferredcites →https://doi.org/10.1207/s15327906mbr3804_4openalex-snapshot
Investigation and Treatment of Missing Item Scores in Test and Questionnaire Data
inferredcites →https://doi.org/10.3390/en10101520openalex-snapshot
Combining a Genetic Algorithm and Support Vector Machine to Study the Factors Influencing CO2 Emissions in Beijing with Scenario Analysis
inferredcites →https://doi.org/10.5281/zenodo.14823054openalex-snapshot
FUZZY MAP APPROACH FOR ACCRUING VELOCITY OF BIG DATA
inferredcites →https://doi.org/10.5555/1756006.1756012openalex-snapshot
An Investigation of Missing Data Methods for Classification Trees Applied to Binary Response Data

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Hybrid GAIN-Based Spacecraft Anomaly Detection via Reconstruction of Randomly Missing Data*
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inferred← citeshttps://doi.org/10.1109/icaica54878.2022.9844522openalex-snapshot
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Big Data, Classification, Clustering and Generate Rules: An inevitably intertwined for Prediction
inferred← citeshttps://doi.org/10.1109/icssit53264.2022.9716355openalex-snapshot
Study on Missing Values and Outlier Detection in Concurrence with Data Quality Enhancement for Efficient Data Processing
inferred← citeshttps://doi.org/10.11113/mjfas.v19n6.3098openalex-snapshot
Impact of Missing Data on Correlation Coefficient Values: Deletion and Imputation Methods for Data Preparation
inferred← citeshttps://doi.org/10.1155/2021/3870147openalex-snapshot
An Approach to Acquire the Constraints Using Panel Big Data Hybrid Association Rule and Discretization Process for Breast Cancer Prediction
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Prediction of accessibility testing using a generalized linear model for e-government
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Application of Machine Learning Methods for Gravity Anomaly Prediction
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Failure Prediction Approach in Agile Software Development
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A MISSING DATA IMPUTATION METHOD BASED ON GREY WOLF ALGORITHM FOR DIABETES DISEASE
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A New Approach for Missing Data Imputation in Big Data Interface
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