METHODS AND ALGORITHMS FOR INTELLIGENT DATA ANALYSIS
Abstract
Intelligent Data Analysis (IDA) is a rapidly growing field that integrates techniques from artificial intelligence, machine learning, and statistics to extract meaningful patterns and knowledge from large and complex datasets. This paper explores the main methods and algorithms used in intelligent data analysis, focusing on their theoretical foundations and practical applications. Key approaches such as classification, clustering, regression, and association rule mining are discussed, along with widely used algorithms including decision trees, support vector machines, k-means clustering, neural networks, and ensemble methods.
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