第 2 / 5 页
非代码面试题
显示 20 / 91 道匹配题目
答题状态：未尝试未正确已正确
ID题目领域难度题型进度权限
2412Why Model Rankings Can Flip as n GrowsWhy can a simple model beat a flexible one at small n and then lose badly once n is large?机器学习中等essay未尝试面试订阅2413Why Bagging Mainly Targets VarianceWhy is bagging usually described as a variance-reduction tool rather than a bias-reduction tool?机器学习中等essay未尝试面试订阅2414Why Irreducible Noise Caps the Best Achievable Test ErrorWhy can model improvements stall even after both bias and variance seem small?机器学习困难essay未尝试面试订阅2415Why a Stable but Biased Model May Be Preferred OperationallyWhy might a desk prefer a slightly biased model that behaves predictably over a lower-bias model whose outputs swing wildly retrain to retrain?机器学习困难essay未尝试面试订阅2416Why Learning Curves Diagnose Which Error Source DominatesWhat does it usually mean if training error is low, validation error is much higher, and the gap narrows steadily with more data?机器学习简单essay未尝试免费2417Why Train Error Alone Is a Bad Complexity SelectorWhy is 'pick the model with the lowest train error' a bad rule for model selection?机器学习简单essay未尝试免费2418Why Small Validation Sets Overreact to Complex ModelsWhy can small validation sets make model-comparison results look much noisier for complex models?机器学习中等essay未尝试面试订阅2419Why Low Bias Is Not Automatically DesirableWhy is 'lower bias' not automatically a sufficient argument for preferring one model over another?机器学习中等essay未尝试免费2420Why Deployment Preferences Can Differ From Benchmark-MSE PreferencesWhy can the model that minimizes benchmark MSE fail to be the one a production team actually deploys?机器学习困难essay未尝试面试订阅2422Log-Loss Gap Between Two Positive ForecastsAn event occurs (y=1). Forecast A assigns probability 0.9 and forecast B assigns probability 0.7. By how much is B's log loss larger than A's?机器学习简单数值题未尝试免费2423Weighted Log-Loss Bayes Probability 3For binary Y with P(Y=1|X)=p, consider weighted log-loss L(q,Y) = -alpha Y ln q - beta (1-Y) ln(1-q). What probability q minimizes the conditional expected loss?机器学习中等derivation未尝试免费2425Why Asymmetric Loss Changes the Optimal Prediction 21Why does changing the relative penalty on overprediction versus underprediction generally move the Bayes act away from the conditional mean?机器学习困难essay未尝试面试订阅2427Decision Threshold Under Asymmetric Classification CostA false negative costs 5 and a false positive costs 1. If p is the predicted probability of the positive class, above what threshold should you classify as positive?机器学习中等derivation未尝试面试订阅2428Weighted-Absolute-Loss Constant ForecastDemand Y takes values 0, 2, and 5 with probabilities 0.5, 0.3, and 0.2. Under a loss of 3(Y-a) + + 1(a-Y) +, what constant forecast a minimizes expected loss?机器学习中等derivation未尝试面试订阅2429Total Huber Loss on a Residual SetUsing Huber loss with delta = 1, compute the total loss on residuals 0.5, -1.2, and 3.0.机器学习中等数值题未尝试面试订阅2431Pseudo-Huber Gradient 8For pseudo-Huber loss ell(r)=delta 2(sqrt(1+(r/delta) 2)-1), derive d ell / d r.机器学习简单derivation未尝试免费2432Squared-Loss Bayes Act for a Discrete TargetY takes values 1, 1, 4, and 7 with equal probability. What constant forecast minimizes expected squared loss?机器学习简单derivation未尝试免费2435Why Log-Loss Punishes Overconfidence More Than Brier LossWhy does log-loss react much more harshly than Brier loss when a model assigns near-certainty to the wrong class?机器学习困难essay未尝试面试订阅2437Why Huber Sits Between Squared and Absolute LossWhy is Huber loss often described as sitting 'between' squared loss and absolute loss?机器学习中等essay未尝试面试订阅2438Why Convexity Makes Averaging Predictions SafeWhy does convexity of a loss function support the intuition that averaging similar predictors often cannot hurt too much?机器学习困难essay未尝试面试订阅