5 天前 - … , support vector machine, principal component regression and partial least squares
regression … SVR uses a subset of training points, or support vectors, in the decision function …

9 天前 - … machine learning algorithms Support Vector Regression (… Machine Regressor
(LGBM), and Linear Regression (LR) in … knowledge of machine learning applications in hydrology …

15 天前 - … The use of foam, as the most economical soil conditioning … regression analysis,
M5Prime decision tree, artificial neural network, and least squares support vector machine …

22 天前 - … 44 which is important for many applications, including crop growth models… sum of
squared errors 982 SVM support vector machine 983 XGB extreme gradient boosting machine …

35 天前 - … The study's main goal is to use various machine learning techniques to improve
reliable and … apply. We use cookies to help provide and enhance our service and tailor content. …

37 天前 - … machine learning algorithms Support Vector Regression (… Machine Regressor
(LGBM), and Linear Regression (LR) in … knowledge of machine learning applications in hydrology …

44 天前 - … to use HSI systems and machine learning models to estimate both energy and
macronutrient content. However, the accuracy of the models will depend on which macronutrient …

46 天前 - … ; Decision Trees, Support Vector Machines, Neural … Least Squares (PLS) regression.
It combines elements from principal component analysis and multiple linear regression (…

49 天前 - … Throughout the paper, we will use the following notations. Probability under the true
… n-consistent for σ2, where ˆθ is the least square estimator or a ridge-regression estimator …

55 天前 - … Linear partial least squares-discriminant analysis (PLS-DA), K-Nearest Neighbor
(KNN) and support vector machine (SVM)… through the application of hyperspectral technology. …