[[["เข้าใจง่าย","easyToUnderstand","thumb-up"],["แก้ปัญหาของฉันได้","solvedMyProblem","thumb-up"],["อื่นๆ","otherUp","thumb-up"]],[["ไม่มีข้อมูลที่ฉันต้องการ","missingTheInformationINeed","thumb-down"],["ซับซ้อนเกินไป/มีหลายขั้นตอนมากเกินไป","tooComplicatedTooManySteps","thumb-down"],["ล้าสมัย","outOfDate","thumb-down"],["ปัญหาเกี่ยวกับการแปล","translationIssue","thumb-down"],["ตัวอย่าง/ปัญหาเกี่ยวกับโค้ด","samplesCodeIssue","thumb-down"],["อื่นๆ","otherDown","thumb-down"]],["อัปเดตล่าสุด 2025-04-30 UTC"],[[["The \"wisdom of the crowd\" suggests that collective opinions can provide surprisingly accurate judgments, as demonstrated by a 1906 ox weight-guessing competition where the collective guess was remarkably close to the true weight."],["This phenomenon can be explained by the Central Limit Theorem, which states that the average of multiple independent estimates tends to converge towards the true value."],["In machine learning, ensembles leverage this principle by combining predictions from multiple models, improving overall accuracy when individual models are sufficiently diverse and reasonably accurate."],["While ensembles require more computational resources, their enhanced predictive performance often outweighs the added cost, especially when individual models are carefully selected and combined."],["Achieving optimal ensemble performance involves striking a balance between ensuring model independence to avoid redundant predictions and maintaining the individual quality of sub-models for overall accuracy."]]],[]]
