Convex Regression with Interpretable Sharp Partitions.

Ashley Petersen, Noah Simon, Daniela Witten

Abstract read

In one paragraph

Article in Journal of machine learning research : JMLR, 2016. 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.

Adaptive nonparametric regression with theBiometrika · 2020
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.

Ashley PetersenDepartment of Biostatistics, University of Washington, Seattle, WA 98195.

Noah SimonDepartment of Biostatistics, University of Washington, Seattle, WA 98195.

Daniela WittenDepartments of Biostatistics and Statistics, University of Washington, Seattle, WA 98195.

Funding

High-dimensional unsupervised learning, with applications to genomicsDP5OD009145 · OD · UNIVERSITY OF WASHINGTON · PI WITTEN, DANIELA · 2011 to 2015

$1.8M

Data-Driven Statistical Learning with Applications to GenomicsDP5OD019820 · OD · UNIVERSITY OF WASHINGTON · PI SIMON, NOAH · 2014 to 2018

$1.7M

NIH HHS DP5 OD009145NIH HHS DP5 OD019820

6 · The paper itself

Abstract

We consider the problem of predicting an outcome variable on the basis of a small number of covariates, using an interpretable yet non-additive model. We propose

Indexed as

convex optimizationinterpretabilitynon-additivitynon-parametric regressionprediction

Identifiers

PMID27635120

PMCPMC5021451

What OpenQuestion holds

Textmetadata

LicenceTDM

Read underepoch 390

Registered trials

None linked

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.