Feature Selection based on the Local Lift Dependence Scale.

Diego Marcondes, Adilson Simonis, Junior Barrera

Abstract read

In one paragraph

Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Overview of the 37th MaxEnt.Entropy (Basel, Switzerland) · 2018
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Diego MarcondesInstitute of Mathematics and Statistics, University of São Paulo, São Paulo 05508-090, Brazil.ORCID 0000-0002-6087-4821

Adilson SimonisInstitute of Mathematics and Statistics, University of São Paulo, São Paulo 05508-090, Brazil.

Junior BarreraInstitute of Mathematics and Statistics, University of São Paulo, São Paulo 05508-090, Brazil.

Funding

Fundação de Amparo à Pesquisa do Estado de São Paulo 2013/07467-1Fundação de Amparo à Pesquisa do Estado de São Paulo 2015/01587-0

6 · The paper itself

Abstract

This paper uses a classical approach to feature selection: minimization of a cost function applied on estimated joint distributions. However, in this new formulation, the optimization search space is extended. The original search space is the Boolean lattice of features sets (BLFS), while the extended one is a collection of Boolean lattices of ordered pairs (CBLOP), that is (features, associated value), indexed by the elements of the BLFS. In this approach, we may not only select the features that are most related to a variable

Indexed as

feature selectionlocal lift dependence scalemutual informationvariable dependencevariable selection

Identifiers

PMID33265188

DOI10.3390/e20020097

PMCPMC7512664

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.