Assessing and Improving Prediction and Classification

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Focusing on the evaluation and enhancement of prediction and classification models, this book offers advanced techniques to accurately assess real-world performance. It covers state-of-the-art algorithms, including committee-based decision making, dataset resampling, and boosting, to improve model robustness. Readers will learn essential methods for building effective models and quantifying their expected behavior in practical applications, ensuring reliable outcomes in various scenarios.