Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 285

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Entropy nets: from decision trees to neural networks

Sethi, I.K.·1990·Proceedings of the IEEE

Abstract

How the mapping of decision trees into a multilayer neural network structure can be exploited for the systematic design of a class of layered neural networks, called entropy nets (which have far fewer connections), is shown. Several important issues such as the automatic tree generation, incorporation of the incremental learning, and the generalization of knowledge acquired during the tree design phase are discussed. A two-step methodology for designing entropy networks is presented. The methodology specifies the number of neurons needed in each layer, along with the desired output, thereby leading to a faster progressive training procedure that allows each layer to be trained separately. Two examples are presented to show the success of neural network design through decision-tree mapping.>

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/5.58346

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 4 references

Cited by

See all 285

Metadata

Authors
Sethi, I. K.
Venue
Proceedings of the IEEE
Published
1990
Volume
78
Issue
10
Pages
1605-1613
ISSN
0018-9219 (ISSN-L)
OpenAlex
W2081136789
Cited by
285
References
4
FWCI
8.31
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Entropy nets: from decision trees to neural networks. https://app.cochat.ai/papers/10.1109/5.58346
The paper
Sethi, I. K. (1990). Entropy nets: from decision trees to neural networks. Proceedings of the IEEE. https://doi.org/10.1109/5.58346

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.