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Machine Learning Algorithms Are Not One-Size-Fits-All

Machine Learning Algorithms Are Not One-Size-Fits-All (New Cyber Technologies)

Machine learning algorithms are broadly categorized under four types of learning problems. Supervised Learning Supervised learning trains the algorithm based on example sets of input/output pairs. Unsupervised Learning Unsupervised learning uses data that has not been labeled, classified or categorized. Reinforcement Learning Unlike the other three types of learning problems, reinforcement learning seeks the optimal path to a desired result by rewarding improvement. Problem Type and Training Data Another, broader categorization of algorithm is based on the type of problem, such as classification, regression, anomaly detection or dimensionality reduction. Other Considerations for Selecting Machine Learning Algorithms Data type also dictates the choice of algorithm because some algorithms work better on certain data types than others.

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