بدائل البحث:
complex optimization » convex optimization (توسيع البحث), whale optimization (توسيع البحث), codon optimization (توسيع البحث)
wolf optimization » whale optimization (توسيع البحث), swarm optimization (توسيع البحث), _ optimization (توسيع البحث)
based complex » layer complex (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based wolf » based whole (توسيع البحث), based work (توسيع البحث), based well (توسيع البحث)
complex optimization » convex optimization (توسيع البحث), whale optimization (توسيع البحث), codon optimization (توسيع البحث)
wolf optimization » whale optimization (توسيع البحث), swarm optimization (توسيع البحث), _ optimization (توسيع البحث)
based complex » layer complex (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based wolf » based whole (توسيع البحث), based work (توسيع البحث), based well (توسيع البحث)
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81
Supplementary Material 8
منشور في 2025"…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"
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82
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Despite the increased complexity associated with binary classification, it remained more efficient, offering higher classification accuracy for samples and facilitating the selection of the most relevant time or variables, such as cooking time ≤ 30 minutes. …"
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83
Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Despite the increased complexity associated with binary classification, it remained more efficient, offering higher classification accuracy for samples and facilitating the selection of the most relevant time or variables, such as cooking time ≤ 30 minutes. …"