第 59 / 87 页
非代码面试题
显示 20 / 1721 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
4367Nested CV Fit Count 2A search grid contains 4 learning rates, 3 tree depths, and 5 regularization strengths. How many hyperparameter combinations are in the grid?机器学习简单数值题未尝试面试订阅4368Nested CV Fit Count 3Successive halving starts with 27 configurations. Each round keeps one third of the configurations and evaluates all survivors once. If you run three rounds total, how many model fits are executed?机器学习简单数值题未尝试面试订阅4369Nested CV Fit Count 4You compare 12 hyperparameter settings with 5-fold CV repeated 3 times. How many validation scores are produced in total across all settings and folds?机器学习简单数值题未尝试面试订阅4370Nested CV Fit Count 5A time-series hyperparameter sweep evaluates 8 settings on 6 expanding-window splits. If each setting is refit once per split, how many model fits are needed?机器学习简单数值题未尝试面试订阅4371Successive Halving Budget 1A grid over regularization strength C expands from 5 log-spaced values to 9 log-spaced values, while all other settings stay fixed. If you use 4 values for another hyperparameter and 6-fold CV, how many additional model fits does the denser C grid create?机器学习中等数值题未尝试面试订阅4372Successive Halving Budget 2A random search draws 20 configurations independently, and the genuinely good region occupies 8% of the hyperparameter space. What is the probability of hitting that region at least once?机器学习中等数值题未尝试面试订阅4373Successive Halving Budget 3Successive halving starts with 64 configurations. Compare two keep ratios over three rounds total: keep one half each round versus keep one quarter each round. How many fewer fits does the one-quarter schedule use?机器学习中等数值题未尝试面试订阅4374Successive Halving Budget 4A tuning run tests 30 configurations. Switching from 10-fold CV to 5-fold CV while keeping the configuration set fixed saves how many model fits?机器学习中等数值题未尝试面试订阅4375Successive Halving Budget 5A random-search budget increases from 40 to 55 configurations. Each configuration uses 4-fold CV, and each fit takes 12 minutes. How much extra wall-clock training time is implied if runs are serial?机器学习中等数值题未尝试面试订阅4391Return Feature Alignment 1A stock closes at 100 yesterday, opens at 102 today, and closes at 101 today. What are the overnight return and the intraday return for today?机器学习简单数值题未尝试面试订阅4392Return Feature Alignment 2A stock returns 1.4% today while the benchmark returns 0.5%. If the stock's beta to the benchmark is 1.6, what market-adjusted residual return do you attribute to the stock?机器学习简单数值题未尝试面试订阅4393Return Feature Alignment 3At today's close, you build a leakage-safe trailing-mean return feature from the last five completed daily returns: [1%, -2%, 0%, 3%, 2%]. What feature value do you store?机器学习简单数值题未尝试面试订阅4394Return Feature Alignment 4A realized-volatility feature is defined as the root-mean-square of the last four daily returns. If those returns are [1%, -1%, 2%, 0%], what realized volatility feature do you get?机器学习简单数值题未尝试面试订阅4395Return Feature Alignment 5A momentum feature is defined as trailing 20-day cumulative return divided by trailing daily volatility. If cumulative return is 6% and daily volatility is 1.5%, what vol-scaled momentum value do you store?机器学习简单数值题未尝试面试订阅4396Cross-Sectional Z-Score 1If today's close is 100, tomorrow's open is 98, and tomorrow's close is 99, what is the next-day open-to-close return that would be used as an intraday label available after tomorrow's session?机器学习简单数值题未尝试面试订阅4397Cross-Sectional Z-Score 2An asset returns 1.2% today while the cross-sectional mean return of its universe is 0.4%. What demeaned return feature does the asset receive?机器学习简单数值题未尝试面试订阅4398Cross-Sectional Z-Score 3A stock returns 1.5% while its sector index returns 0.9%. If the stock's sector beta is 1.2, what sector-residual return feature do you compute?机器学习简单数值题未尝试面试订阅4399Cross-Sectional Z-Score 4Yesterday's return was 1.8%. The trailing mean of completed daily returns is 0.3% and the trailing standard deviation is 0.5%. What lagged return z-score feature do you record?机器学习简单数值题未尝试面试订阅4400Cross-Sectional Z-Score 5A stock closes at 50 yesterday and opens at 51 today, while the market index closes at 2000 yesterday and opens at 2020 today. If the stock's overnight beta to the market is 1.5, what market-adjusted overnight return feature do you compute?机器学习简单数值题未尝试面试订阅4416Walk-Forward Tradable Coverage 1A rolling walk-forward scheme uses 24 months of training, then a 1-month embargo, then 6 months of testing, and advances by 6 months each time across 61 months of history. In each test block, the first 2 months are used only to warm up a trailing feature, so they are not tradable. How many tradable out-of-sample months do you score in total?机器学习简单数值题未尝试面试订阅