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Feature engineering

In supervised machine learning and statistical modeling, feature engineering is a preprocessing step which transforms raw data into a more effective set of inputs. Each input comprises several attributes, known as features. By providing models with relevant information, feature engineering significantly enhances their predictive accuracy and…

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Overview

Clustering

Predictive modelling

Automation

Feature stores

Alternatives

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Map overview Semantic statistics

Feature engineering

Nodes37
Edges36
Triples58
Avg. degree1.95
Density0.054054
Components1

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Feature engineering

Top relations

related to Clustering · 16
Feature engineering → An, Consensus Matrix Decomposition, Especially, MCMD, Multi-view Classification, NMF, NMTF, Non-Negative Matrix Factorization, Non-Negative Matrix-Tri Factorization, Non-Negative Tensor Decomposition/Factorization, NTF/NTD, One, Other, Several, The, These
related to Open-source implementations · 10
Feature engineering → An, C/C, Despite, It, MCMD, On, One-Button Machine, OneBM, Python, There
related to Predictive modelling · 10
Feature engineering → Even, Feature, Features, ICA, Independent Component Analysis, Key, LDA, Linear Discriminant Analysis, PCA, Principal Components Analysis
related to Automation · 6
Feature engineering → Automation, Deep Feature Synthesis, Machine, MRDTL, Multi-relational Decision Tree Learning, Related
related to Alternatives · 4
Feature engineering → Deep, Feature, However, In
is a · 2
Feature engineering → preprocessing step which transforms raw data into a more effective set of inputs, research topic that dates back to the 1990s

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Important terminology

feature data engineering features learning time python machine clustering series deep used matrix include algorithms datasets model training relational set

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Feature engineeringis apreprocessing step which transforms raw data into a more effective set of inputs0.90text
Feature engineeringis aresearch topic that dates back to the 1990s0.90text
the Reynolds number in fluid dynamicsinstance ofphysicists construct dimensionless numbers0.80text
the Nusselt number in heat transferinstance ofphysicists construct dimensionless numbers0.80text
and the Archimedes number in sedimentationinstance ofphysicists construct dimensionless numbers0.80text
regularizationinstance ofFeature templates - implementing feature templates instead of coding new featuresFeature combinations - combinations that cannot be represented by a linear systemFeature explosi…0.80text
kernel methodsinstance ofFeature templates - implementing feature templates instead of coding new featuresFeature combinations - combinations that cannot be represented by a linear systemFeature explosi…0.80text
and feature selectioninstance ofFeature templates - implementing feature templates instead of coding new featuresFeature combinations - combinations that cannot be represented by a linear systemFeature explosi…0.80text
tuple id propagation.Open-source implementationsThere are a number of open-source librariesinstance ofThese redundancies can be reduced by using techniques0.80text
tools that automate feature engineering on relational datainstance ofThese redundancies can be reduced by using techniques0.80text
time seriesinstance ofThese redundancies can be reduced by using techniques0.80text
tuple id propagationinstance ofThese redundancies can be reduced by using techniques0.80text

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