Weak Learner Vs. Strong Learner Table Of Contents: Introduction. Weak Learner. Strong Learner. Conclusion. (1) Introduction: In machine learning, the terms “strong learner” and “weak learner” refer to the performance and complexity of predictive models within an ensemble or learning algorithm. These terms are often used in the context of boosting algorithms. (2) Weak Learner: A weak learner is a model that performs slightly better than random guessing or has limited predictive power on its own. Weak learners are typically simple and have low complexity, such as decision stumps (a decision tree with only one split), shallow decision trees, or

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