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4178Winsorize-then-Standardize PipelineA raw daily return of 4.8% is winsorized to the range [-3%, 3%], then standardized using trailing mean 0.5% and trailing standard deviation 1.0%. What z-score feature results?机器学习简单数值题未尝试面试订阅4179Log1p Volume TransformA liquidity feature uses log1p(volume). If today's volume is 999999 shares, what transformed value do you store?机器学习简单数值题未尝试面试订阅4180Leakage-Safe Rolling Mean FeatureAt today's open you build a leakage-safe rolling-mean return feature from the last four completed daily returns: [1.0%, -2.0%, 0.5%, 1.5%]. What feature value do you use?机器学习简单数值题未尝试面试订阅4191Hyperplane Score and Margin 1Using the polynomial kernel K(x,z)=(x·z+1) 2, what is K((1,2),(2,0))?机器学习中等数值题未尝试面试订阅4192Hyperplane Score and Margin 2An RBF SVM uses K(x,z)=exp(-γ||x-z|| 2) with γ=0.5. If ||x-z|| 2=4, what kernel similarity is produced?机器学习中等数值题未尝试面试订阅4193Hyperplane Score and Margin 3For a soft-margin SVM, a training point has label y=1 and score f(x)=0.3. What hinge loss max(0,1-yf(x)) does it incur?机器学习中等数值题未尝试面试订阅4194Hyperplane Score and Margin 4A soft-margin SVM uses objective 0.5||w|| 2 + C Σ hinge i. If one point has hinge loss 1.2 and C=2, what penalty contribution does that point add to the objective?机器学习中等数值题未尝试面试订阅4195Hyperplane Score and Margin 5If a linear SVM has ||w||=5, what is the geometric margin width 2/||w||?机器学习中等数值题未尝试面试订阅4196Kernel Decision Function Evaluation 1A kernel SVM prediction uses two support vectors. Their signed contributions at a test point are +1.2 and -0.4, and the bias is -0.1. What score and predicted class result?机器学习中等数值题未尝试面试订阅4198Kernel Decision Function Evaluation 3Using the degree-3 polynomial kernel K(x,z)=(x·z+1) 3, what is K((1,1),(2,-1))?机器学习中等数值题未尝试面试订阅4216Normalized MDI Share 1A random forest reports total mean-decrease-in-impurity contributions spread=0.42, imbalance=0.21, id bucket=0.07. What are the normalized importance shares, and which feature ranks first?机器学习简单数值题未尝试面试订阅4217Normalized MDI Share 2A model has baseline validation AUC 0.62. After permuting three features separately, AUC becomes 0.57 for value signal, 0.60 for momentum, and 0.61 for zip code. What permutation-importance drops do these imply, and which feature ranks first?机器学习简单数值题未尝试面试订阅4218Normalized MDI Share 3A sector feature is represented by three one-hot columns with impurity-gain importances 0.04, 0.03, and 0.01. Two other features have importances 0.05 and 0.07. If you aggregate the one-hot block into a single group, what are the normalized group shares and which group ranks first?机器学习简单数值题未尝试面试订阅4219Normalized MDI Share 4Two trees contribute split gains to features A and B. Tree 1 contributes A=12, B=5. Tree 2 contributes A=8, B=10. What are the total normalized gain importances for A and B?机器学习简单数值题未尝试面试订阅4220Normalized MDI Share 5A model has baseline log loss 0.400. After permuting feature X, log loss rises to 0.455; after permuting feature Y, it rises to 0.420. What are the permutation importances under a log-loss metric, and which feature is more important?机器学习简单数值题未尝试面试订阅4221Grouped Permutation Drop Pattern 1A model starts at validation accuracy 0.82. Permuting feature X1 alone lowers it to 0.79, permuting X2 alone lowers it to 0.8, and permuting them together lowers it to 0.7. What are the three drops, and what pattern does that suggest?机器学习中等数值题未尝试面试订阅4223Grouped Permutation Drop Pattern 3A model has baseline AUC 0.70. With a correlated twin present, permuting feature A drops AUC to 0.64. After removing the twin, permuting A drops AUC to 0.58. By how much did feature A's permutation importance increase?机器学习中等数值题未尝试面试订阅4224Grouped Permutation Drop Pattern 4An impurity-based feature ranking is id hash=0.40, signal 1=0.35, signal 2=0.25. After limiting max depth, id hash gain is cut in half while the other raw gains are unchanged. What are the new normalized shares?机器学习中等数值题未尝试面试订阅4225Grouped Permutation Drop Pattern 5A feature's permutation importance is measured as baseline accuracy minus permuted accuracy. Under validation set A the numbers are 0.80 and 0.78; under noisier validation set B they are 0.74 and 0.72. What is the relative drop as a percentage of baseline in each case?机器学习中等数值题未尝试面试订阅4241First Principal Direction from 2x2 Covariance 1A centered two-feature dataset has covariance matrix [[4.2, 1.6], [1.6, 1.8]]. What is the first principal-component direction and its variance?机器学习中等数值题未尝试面试订阅