Data Preprocessing

Data Preprocessing is a foundational step in data analysis and machine learning that involves transforming raw data into a clean, consistent, and structured format suitable for mining and predictive modeling by applying techniques such as cleaning, integration, transformation, and reduction.

9.3K

Publications

748.6K

Citations

23.4K

Authors

5K

Institutions

Publications per year

2017–2026

3.6K

Authors

23.4K

  1. FH
    Francisco Herrera

    Universidad de Granada, Spain

    54 publications · 13.4K citations

    37

    h-index

  2. WP
    Witold Pedrycz

    University of Alberta, Canada

    69 publications · 5.1K citations

    37

    h-index

  3. TH
    Tzung‐Pei Hong

    National University of Kaohsiung, Taiwan

    50 publications · 2.8K citations

    30

    h-index

  4. TL
    Tianrui Li

    Southwest Jiaotong University, China

    30 publications · 2.3K citations

    24

    h-index

  5. UY
    Unil Yun

    Sejong University, South Korea

    27 publications · 1.6K citations

    23

    h-index

1–5 of 23.4K

Venues

  1. Expert Systems with Applications

    305 publications · 18.1K citations

    71

    h-index

  2. Information Sciences

    204 publications · 14.4K citations

    66

    h-index

  3. Fuzzy Sets and Systems

    130 publications · 16.4K citations

    63

    h-index

  4. Knowledge-Based Systems

    162 publications · 10.3K citations

    57

    h-index

  5. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 73 publications · 20.8K citations

    46

    h-index

1–5