Data Binning

Data Binning is a data preprocessing technique that partitions continuous or discrete data values into a finite set of contiguous intervals or categories, known as bins, to reduce noise, enhance interpretation, and facilitate subsequent analysis.

129

Publications

12.1K

Citations

383

Authors

204

Institutions

Publications per year

2017–2026

41

Variants

Data Bucketing

Authors

383

  1. MD
    Matias D. Cattaneo

    University of Michigan, United States

    5 publications · 688 citations

    5

    h-index

  2. YF
    Yingjie Feng

    Princeton University, United States

    4 publications · 221 citations

    4

    h-index

  3. RK
    Richard K. Crump

    Federal Reserve Bank of New York, United States

    4 publications · 221 citations

    4

    h-index

  4. MH
    Max H. Farrell

    University of Chicago, United States

    3 publications · 167 citations

    3

    h-index

  5. EK
    Ergina Kavallieratou

    University of the Aegean, Greece

    3 publications · 143 citations

    3

    h-index

1–5 of 383

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 188 citations

    3

    h-index

  2. Cytometry

    3 publications · 291 citations

    3

    h-index

  3. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 3 publications · 159 citations

    3

    h-index

  4. PLoS ONE

    3 publications · 55 citations

    3

    h-index

  5. ESAIM Probability and Statistics

    2 publications · 174 citations

    2

    h-index

1–5