Non-comparison-based Algorithms
Non-comparison-based algorithms are a class of algorithms that do not rely on comparing elements to each other to perform their task. Instead, they use other techniques such as hashing, counting, or indexing to process data. These algorithms are particularly useful when dealing with large datasets, as they can often perform their operations in linear time, rather than the quadratic time required by comparison-based algorithms. Non-comparison-based algorithms are commonly used in data science and artificial intelligence applications, such as clustering, classification, and recommendation systems.
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