Similarity-Based Data-Fusion Schemes for Missing Data Imputation in Univariate Time Series Data

S. Nickolas; K. Shobha

doi:10.1007/978-981-15-7533-4_12

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Similarity-Based Data-Fusion Schemes for Missing Data Imputation in Univariate Time Series Data

S. Nickolas K. Shobha

Year: 2021 Algorithms for intelligent systems Pages: 149-165 Publisher: Springer Nature

DOI: 10.1007/978-981-15-7533-4_12

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Keywords:

Imputation (statistics) Missing data Univariate Data mining Computer science Cluster analysis Data set Time series Statistics Multivariate statistics Mathematics Artificial intelligence Machine learning

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Time Series Analysis and Forecasting

Physical Sciences → Computer Science → Signal Processing

Traffic Prediction and Management Techniques

Physical Sciences → Engineering → Building and Construction

Advanced Clustering Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Similarity-Based Data-Fusion Schemes for Missing Data Imputation in Univariate Time Series Data

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