Ensemble Methods by Zhi-Hua Zhou (Author)

Dimensions:

176 mm × 250 mm

17.6 cm × 25 cm

6.93 inches × 9.84 inches

Ensemble methods that train multiple learners and then combine them to use, with Boosting and Bagging as representatives, are well-known machine learning approaches. It has become common sense that an ensemble is usually significantly more accurate than a single learner, and ensemble methods have already achieved great success in various real-world tasks.