Search Results - random matrices

Graphical approaches to support the analysis of linear-multilevel models of lamb pre-weaning growth in Kolda (Senegal) by Lancelot, R., Lesnoff, Matthieu, Tillard, E., McDermott, John J.

“…The structure of the random-effects variance-covariance matrices were blocked-diagonal at the herd level and unstructured at the lamb level. …”
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Document subject matrix as a factor of precision in computerized information systems by Azubuike, A.A.

“…It has been found that the subject matrix of a document - the pattern of relationships existing between the array of the subjects used as its descriptors - determines the chances of the document being relevant to the question for which it is retrieved. The subject matrices of most documents are such that interference of terms which result in fallouts would occur if coordination is done without recourse to the relationships existing between its descriptors as is the case when Boolean 'AND' is used in retrieval of when random pre-coordination takes place. …”
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Which machine learning algorithm is best suited for estimating reference evapotranspiration in humid subtropical climate? by Deb, P., Kumar, V., Urfels, A., Lautze, Jonathan F., Kamboj, B. R., Sharma, J. R., Yadav, S.

“…In this study, four Gaussian process regression (GPR) algorithms—polynomial kernel (PK), polynomial universal function kernel (PUK), normalized poly kernel (NPK), and radial basis function (RBF)—were compared against widely used random forest (RF) and a simpler locally weighted linear regression (LWLR) algorithm at a humid subtropical region in India. …”
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Efecto del clima sobre la respuesta térmica en vacas de diferentes grupos raciales en trópico bajo by Molina-Benavides, Raúl Andrés, Perilla-Duque, Sandra, Campos-Gaona, Rómulo, Sánchez-Guerrero, Hugo, Rivera-Palacio, Juan Camilo, Muñoz-Borja, Luis Armando, Jiménez-Rodas, Daniel

“…The information was analyzed using descriptive statistics, correlation matrices and Random Forest models, through the R software. …”
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Comparison of forest fire severity classification models based on aerial images and Landsat 8 OLI/TIRS images of a forest fire area in central Sweden by Straker, Adrian

“…The performances of all created models were assessed by the application of all models on test data sets, the generation of confusion matrices and finally the computation of the overall accuracy and the Cohen´s Kappa values. …”
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A correlation structure for the analysis of Gaussian and non-Gaussian responses in crossover experimental designs with repeated measures by Martinez Niño, Carlos Alberto, Cruz, N. A., Melo, O. O.

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A correlation structure for the analysis of Gaussian and non-Gaussian responses in crossover experimental designs with repeated measures by Cruz, N. A., Melo, O. O., Martinez, C. A.

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Quantitative genetics and genomics converge to accelerate forest tree breeding by Grattapaglia, Dario, Silva Junior, Orzenil B., Resende, Rafael T., Cappa, Eduardo Pablo, Müller, Bárbara S. F., Tan, Biyue, Isik, Fikret, Ratcliffe, Blaise, El-Kassaby, Yousry A.

“…Realized genomic relationships matrices, on the other hand, provide innovations in genetic parameters’ estimation and breeding approaches by tracking the variation arising from random Mendelian segregation in pedigrees. …”
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Estimation of forage biomass in oat (Avena sativa) using agronomic variables through UAV multispectral imaging by Urquizo Barrera, Julio Cesar, Ccopi Trucios, Dennis, Ortega Quispe, Kevin, Castañeda Tinco, Italo, Patricio Rosales, Solanch, Passuni Huayta, Jorge, Figueroa Venegas, Deyanira, Enriquez Pinedo, Lucia, Ore Aquino, Zoila, Pizarro Carcausto, Samuel

“…The Random Forest model showed the best performance, with a coefficient of determination R2 of 0.52 on the test set, followed by Support Vector Machines with an R2 of 0.50. …”
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Assessing the prospects of remote sensing maize leaf area index using UAV-derived multi-spectral data in smallholder farms across the growing season by Buthelezi, S., Mutanga, O., Sibanda, M., Odindi, J., Clulow, A.D., Chimonyo, Vimbayi Grace Petrova, Mabhaudhi, Tafadzwanashe

“…Maize LAI samples were collected across the growing season, a Random Forest (RF) regression ensemble based on UAV spectral data and the collected maize LAI samples was used to estimate maize LAI. …”
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Estimation of height and aerial biomass in Eucalyptus globulus plantations using UAV-LiDAR by Enriquez Pinedo, Lucía, Ortega Quispe, Kevin, Ccopi Trucios, Dennis, Urquizo Barrera, Julio, Rios Chavarría, Claudia, Pizarro Carcausto, Samuel, Matos Calderon, Diana, Patricio Rosales, Solanch, Rodríguez Cerrón, Mauro, Ore Aquino, Zoila, Paz Monge, Michel, Castañeda Tinco, Italo

“…The findings revealed that the combination of LiDAR with advanced statistical techniques, such as multiple regression and Random Forest, significantly improves the accuracy of biomass estimation, surpassing traditional methods based on allometric equations. …”
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Preferencias de Scirtothrips dorsalis Hood 1919 (Thysanoptera: Thripidae) por diferentes estructuras de la planta del algodón (Gossypium hirsutum L.) en el valle cálido del Magdale... by Ebratt, Everth, Rodríguez, Andrés, Monje, Buenaventura, Varón, Edgar, Brochero, Helena, Goldarazena, Arturo

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