Which algorithm is most suitable for solving optimization problems in Numerical and Statistical Computing?
Gradient Descent is a widely used optimization algorithm in numerical and statistical computing. It is designed to find the minimum of a function by iteratively moving in the direction of the steepest descent, as defined by the negative gradient. This algorithm is essential for training various machine learning models, especially those involving optimization problems where the goal is to minimize a cost or loss function. Why Other Options are Wrong: b) K-Means Clustering is used for clustering data rather than optimization. c) Decision Trees are used for classification and regression tasks, not for optimization problems. d) Genetic Algorithms are heuristic search algorithms inspired by natural selection and can solve optimization problems but are not as widely used as Gradient Descent for many numerical problems. e) Support Vector Machines (SVM) are used for classification and regression tasks, not specifically for solving optimization problems.
Which is the type of tillage in which number of tillage operations are reduced to minimum required?
____ is used for measuring the draft of agricultural implements.
Rose supreme is the variety of
‘Kresek’ symptom is a characteristic symptom of which disease of rice?
Which one of the following is C 4Plant?
Which of the following is not naturally distributed in India?
Which disease is known as rice fever disease or rich men’s disease?
The process of loosening the edible part of grain (or other crop) from the straw to which it is attached is known as
Which part of the insect's exoskeleton is composed of living cells?
The term pulsing is related to-