Interpolation Features

Interpolation Features is a time series feature engineering method that generates informative attributes by estimating missing or unobserved values within a temporal sequence using mathematical interpolation techniques, thereby preserving underlying temporal dynamics and enhancing predictive model performance.

4

Publications

85

Citations

13

Authors

8

Institutions

Publications per year

2017–2026

2

Authors

13

  1. RM
    Rytis Maskeliūnas

    Kaunas University of Technology, Lithuania

    1 publications · 48 citations

    1

    h-index

  2. AD
    Aaron D. Knochel

    Pennsylvania State University, United States

    1 publications · 10 citations

    1

    h-index

  3. RC
    Rupal Chaudhari

    Visvesvaraya National Institute of Technology, India

    1 publications · 11 citations

    1

    h-index

  4. AA
    Adebayo Abayomi‐Alli

    Federal University of Agriculture, Nigeria

    1 publications · 48 citations

    1

    h-index

  5. JJ
    Joaquim Jorge

    Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento, Portugal

    1 publications · 10 citations

    1

    h-index

1–5 of 13

Venues

  1. Journal of Logic and Computation

    1 publications · 16 citations

    1

    h-index

  2. 1

    h-index

  3. Annals of Computer Science and Information Systems

    Conference · 1 publications · 48 citations

    1

    h-index

  4. Industrial Management & Data Systems

    1 publications · 13 citations

1–4