ExampleRound3:t=3++十+3 misclassified (with circles):E3 = 0.14 → β3 = 0.92.Previouslycorrectlyclassifieddatapointsarenowmisclassifiedhence our erroris low;what'sthe intuition?Sincetheyhavebeenconsistentlyclassifiedcorrectly,thisround'smistakewillhopefullynothaveahuge impactontheoverall prediction119/22/2026PATTERNRECOGNITION
Example Round 3: t = 3 3 misclassified (with circles): 𝜖3 = 0.14 → 𝛽3 = 0.92. Previously correctly classified data points are now misclassified, hence our error is low; what’s the intuition? ◦ Since they have been consistently classified correctly, this round’s mistake will hopefully not have a huge impact on the overall prediction 9/22/2026 PATTERN RECOGNITION 11
ExampleFinal classifier:combining3classifiers0.42+0.65+0.92signfinal4Alldatapointsarenowclassifiedcorrectly!129/22/2026PATTERNRECOGNITION
Example Final classifier: combining 3 classifiers All data points are now classified correctly! 9/22/2026 PATTERN RECOGNITION 12