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Mantra: a novel imputation measure for disease classification and prediction

Published: 01 October 2018 Publication History

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Abstract

Medical record instances can have missing values which makes them unsuitable for learning process. Data Imputation is normally done to fill one or more missing data attribute values. Imputation helps to perform supervised or un-supervised learning after the dataset is free from missing data. Learning process helps the discovery of hidden, valuable and important information that can provide insightful results. Imputation is a data pre-processing task that requires applying distance function to find missing values. In this paper, a distance function named MANTRA is proposed to impute missing data values. The distance function is also called as the imputation measure since it is designed for imputation of missing values. A working example is demonstrated that shows how imputation is achieved using proposed distance function, MANTRA. It is proved that the nominal value that is filled after imputation is same as the original.

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  • (2022)Modified K-Nearest Neighbour Using Proposed Similarity Fuzzy Measure for Missing Data Imputation on Medical Datasets (MKNNMBI)International Journal of Fuzzy System Applications10.4018/IJFSA.30627811:3(1-15)Online publication date: 5-Aug-2022
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cover image ACM Other conferences
DATA '18: Proceedings of the First International Conference on Data Science, E-learning and Information Systems
October 2018
274 pages
ISBN:9781450365369
DOI:10.1145/3279996
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 01 October 2018

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Author Tags

  1. attribute
  2. computational complexity
  3. distance function
  4. imputation
  5. missing values
  6. novel approach

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  • (2022)Modified K-Nearest Neighbour Using Proposed Similarity Fuzzy Measure for Missing Data Imputation on Medical Datasets (MKNNMBI)International Journal of Fuzzy System Applications10.4018/IJFSA.30627811:3(1-15)Online publication date: 5-Aug-2022
  • (2022)Complex intuitionistic fuzzy ordered weighted distance measureComputational and Applied Mathematics10.1007/s40314-022-02061-441:8Online publication date: 17-Oct-2022
  • (2021)Design and Analysis of activation functions used in deep learning modelsThe 7th International Conference on Engineering & MIS 202110.1145/3492547.3492575(1-5)Online publication date: 11-Oct-2021
  • (2021)Jordanian Higher Basic Stage Students’ uses of the Social Networking Site (Facebook) as a Mediator Assistant in Their LearningThe 7th International Conference on Engineering & MIS 202110.1145/3492547.3492574(1-5)Online publication date: 11-Oct-2021
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  • (2021)Fuzzy Feature Similarity Functions for Feature Clustering and Dimensionality ReductionInternational Conference on Data Science, E-learning and Information Systems 202110.1145/3460620.3460758(219-224)Online publication date: 5-Apr-2021
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