Score breakdown

Random Forests

paper-0043 · paper · 2001

Leo Breiman

The most-used classical ML algorithm in applied practice.

Academic, score 0.1093

MetricStatusValueNorm.WeightContributionSourceConfidenceProvenance
citation_countpresent126295.00.5685020.50.284251OpenAlexhighlink
library_holdingsmissingrecorded as missing, penalized by rule, never imputed−0.1recorded as missing; penalized by rule, never imputed
readership_persistencepresent15.01.00.050.05OpenAlexmediumlink
syllabus_adoptionsmissingrecorded as missing, penalized by rule, never imputed−0.125recorded as missing; penalized by rule, never imputed

Broad Influence, score 0.3137

MetricStatusValueNorm.WeightContributionSourceConfidenceProvenance
citation_countpresent126295.00.5685020.20.1137OpenAlexhighlink
library_holdingsmissingrecorded as missing, penalized by rule, never imputed−0.125recorded as missing; penalized by rule, never imputed
readership_persistencepresent15.01.00.40.4OpenAlexmediumlink
syllabus_adoptionsmissingrecorded as missing, penalized by rule, never imputed−0.075recorded as missing; penalized by rule, never imputed

Governance Practitioner, score -0.0829

MetricStatusValueNorm.WeightContributionSourceConfidenceProvenance
citation_countpresent126295.00.5685020.250.142126OpenAlexhighlink
library_holdingsmissingrecorded as missing, penalized by rule, never imputed−0.15recorded as missing; penalized by rule, never imputed
readership_persistencepresent15.01.00.10.1OpenAlexmediumlink
syllabus_adoptionsmissingrecorded as missing, penalized by rule, never imputed−0.175recorded as missing; penalized by rule, never imputed

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