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The effect of tuning, feature engineering, and feature selection in data mining applied to rainfed sugarcane yield modelling
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Do we need hundreds of classifiers to solve real world classification problems
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inferred← citeshttps://doi.org/10.7287/peerj-cs.1190v0.1/reviews/1openalex-snapshot
Peer Review #1 of "Temporal analysis and opinion dynamics of COVID-19 vaccination tweets using diverse feature engineering techniques (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.1190v0.1/reviews/2openalex-snapshot
Peer Review #2 of "Temporal analysis and opinion dynamics of COVID-19 vaccination tweets using diverse feature engineering techniques (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.1190v0.2/reviews/1openalex-snapshot
Peer Review #1 of "Temporal analysis and opinion dynamics of COVID-19 vaccination tweets using diverse feature engineering techniques (v0.2)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.1190v0.2/reviews/2openalex-snapshot
Peer Review #2 of "Temporal analysis and opinion dynamics of COVID-19 vaccination tweets using diverse feature engineering techniques (v0.2)"
inferred← citeshttps://doi.org/10.7717/peerj-cs.1190openalex-snapshot
Temporal analysis and opinion dynamics of COVID-19 vaccination tweets using diverse feature engineering techniques
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.