Features Of Application Of Error Prediction Models Using Machine Learning
Keywords:
Object set, test set, parameters, prediction, diagnosis, classification. Machine Learning, Supervised Learning, Unsupervised Learning, Reinforcement LearningAbstract
This article, Currently, traditional statistical methods are used in the development of artificial intelligence algorithms and programs. Regression and output interpolation methods have been used based on the values of the given sets. Below are some of the statistical methods that are currently widely used in the development of AI algorithms and programs. Machine Learning (ML) is a field that allows computer systems to learn from data and automate decision-making based on it. This technology plays an important role in the development of artificial intelligence and is used in various fields, including medicine, finance, marketing, and transportation. The main methods of machine learning are: supervised learning, unsupervised learning, reinforcement learning, robustness testing, generative models, deep learning, etc. Each method is used in accordance with different data and tasks. This article analyzes the main methods of machine learning and shows their practical application.
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