AdaBoost in Machine Learning

adaboost is for classifications stumps are weak learners AdaBoost (Adaptive Boosting) is a popular ensemble learning technique that combines the outputs of several weak classifiers to create a strong classifier. Developed by Yoav Freund and Robert Schapire in 1996, AdaBoost works by iteratively training weak learners, typically decision stumps (simple decision trees with one split),…

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XGBoost in Machien Learning

XGBoost (eXtreme Gradient Boosting) is a scalable and efficient implementation of gradient boosting for supervised learning. It has gained popularity for its performance and speed, often winning machine learning competitions. Here are the key concepts and features of XGBoost: Key Concepts: Key Parameters: Example in Python: Here’s a basic example of using XGBoost in Python…

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Ensemble in Machiene Learning

this is about combining multiple models in random forest we use multiple decision trees in boostng we use this methods Ensemble learning is a technique in machine learning where multiple models (often called “weak learners”) are trained to solve the same problem and combined to get better performance. The primary goal of ensemble methods is…

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Markov Decision Process

A Markov Decision Process (MDP) is a mathematical framework for modeling decision-making in situations where outcomes are partly random and partly under the control of a decision-maker. It provides a formalism for modeling the environment in reinforcement learning. An MDP is defined by: The goal in an MDP is to find a policy that maximizes…

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SVM in Machine Learning

SVMs shine with small to medium-sized nonlinear datasets (i.e., hundreds to thousands of instances), especially for classification tasks. this is hyper plane Support Vector Machines (SVM) are a powerful and versatile supervised machine learning algorithm used for classification and regression tasks. They are particularly well-suited for binary classification problems. SVMs work by finding the hyperplane…

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معادلات لاپلاس در ریاضیات مهندسی

پس این معادله لاپلاس میباشد The Laplace equation is a second-order partial differential equation named after the French mathematician Pierre-Simon Laplace. It is commonly used in physics and engineering to describe the behavior of electric, gravitational, and fluid potentials. The equation is given by: $$\nabla^2 \phi = 0$$ or in Cartesian coordinates: $$\frac{\partial^2 \phi}{\partial x^2}…

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IO در پردازنده

اولین روش : Handling I/O (Input/Output) in processors involves several concepts and mechanisms that allow a CPU to interact with external devices such as keyboards, displays, storage devices, and network interfaces. The methods and techniques for handling I/O can vary based on the architecture and specific requirements of the system. Here’s a detailed explanation of…

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