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4 results for Moses Muraya.

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Predictive Modelling of Benign and Malignant Tumors Using Binary Logistic, Support Vector Machine and Extreme Gradient Boosting Models
by Peter Gachoki, Moses Mburu and Moses Muraya
American Journal of Applied Mathematics and Statistics. 2019, 7(6), 196-204. DOI: 10.12691/ajams-7-6-2
Pub. Date: November 26, 2019Views: 18783Downloads: 19419
benign malignant binary logistic support vector machine extreme gradient boosting
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Modelling Plant Growth Based on Gompertz, Logistic Curve, Extreme Gradient Boosting and Light Gradient Boosting Models Using High Dimensional Image Derived Maize (Zea mays L.) Phenomic Data
by Peter Gachoki, Moses Muraya and Gladys Njoroge
American Journal of Applied Mathematics and Statistics. 2022, 10(2), 52-64. DOI: 10.12691/ajams-10-2-3
Pub. Date: August 28, 2022Views: 4020Downloads: 9313
Phenomic data XGBoost Light GBM Gompertz model and logistic function model
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Features Selection in Statistical Classification of High Dimensional Image Derived Maize (Zea Mays L.) Phenomic Data
by Peter Gachoki, Moses Muraya and Gladys Njoroge
American Journal of Applied Mathematics and Statistics. 2022, 10(2), 44-51. DOI: 10.12691/ajams-10-2-2
Pub. Date: June 06, 2022Views: 3296Downloads: 7148
high throughput phenotyping high dimensional data feature extraction feature importance Shapley values LASSO regression
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Advanced Statistical Modelling of Maize Phenotypes Using Compressed Linear Mixed Models in Genome-Wide Association Studies
by Dominic Obare, Moses Muraya and Gladys Njoroge
American Journal of Applied Mathematics and Statistics. 2025, 13(1), 1-13. DOI: 10.12691/ajams-13-1-1
Pub. Date: January 13, 2025Views: 377Downloads: 771
Compressed linear mixed model (CLMM) Phenotypic data genotypic data Single Nucleotide Polymorphism’s (SNPs) R-statistical Software
Abstract Full Text PDF (504 KB) Full Text HTML Full Text ePUB (411 KB)
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