A modified genetic algorithm and weighted principal component analysis based feature selection and extraction strategy in agriculture

Data pre-processing is a technique that transforms the raw data into a useful format for applying machine learning (ML) techniques. Feature selection (FS) and feature extraction (FeExt) form significant components of data pre-processing. FS is the identification of relevant features that enhances th...

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Veröffentlicht in:	Knowledge-based systems Jg. 232; S. 107460
Hauptverfasser:	Aditya Shastry, K., H.A., Sanjay
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 28.11.2021 Elsevier Science Ltd
Schlagworte:	Adaptive systems Agriculture Algorithms Artificial neural networks Attributes Benchmarks Correlation analysis Crop yield Data Data processing Datasets Derivation Extraction Farming Feature extraction Feature selection Fertilizers Fuzzy logic Genetic Algorithm Genetic algorithms Genetics Hybrid Inference Machine learning Model accuracy Neural networks Principal components analysis Support vector machines Trees Weighted-Principal Component Analysis Hybrid Feature extraction Feature selection Weighted-Principal Component Analysis Genetic Algorithm
ISSN:	0950-7051, 1872-7409
Online-Zugang:	Volltext
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