题目4267 · 机器学习
k-Means Assignment Step 2
A 1D cluster currently contains points [1,2,7]. What centroid does k-means assign to that cluster in the update step?
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中文题目题目4268 · 机器学习
k-Means Assignment Step 3
A 2D cluster contains points (0,0), (2,4), and (4,2). What centroid does k-means assign to that cluster?
打开 →题目4272 · 机器学习
k-Means Centroid Update 2
A 1D k-means step has current centroids 0 and 10, and the assigned points are {1,2} to the first cluster and {9} to the second. What are the updated centroids?
打开 →题目4266 · 机器学习
k-Means Assignment Step 1
A point in clustering has average within-cluster distance a=2 and smallest average distance to another cluster b=5. What is its silhouette score?
打开 →题目4269 · 机器学习
k-Means Assignment Step 4
A 2-component GMM has priors 0.6 and 0.4. At point x, the component likelihoods are 0.1 and 0.3. What posterior responsibility does component 2 get?
打开 →题目4270 · 机器学习
k-Means Assignment Step 5
A DBSCAN run uses minPts=5, counting the point itself. A point has 5 neighbors within eps. Is it a core point?
打开 →题目4271 · 机器学习
k-Means Centroid Update 1
In 1D, clusters A={0,2} and B={5,9}. What is their average-linkage distance?
打开 →题目4273 · 机器学习
k-Means Centroid Update 3
A cluster contains points [1,2,4]. What is its within-cluster SSE around the cluster mean?
打开 →题目4274 · 机器学习
k-Means Centroid Update 4
Under Ward linkage, what merge cost increase do two singleton clusters at positions 1 and 4 have in 1D?
打开 →题目4275 · 机器学习
k-Means Centroid Update 5
Clusters A={1,4} and B={6,8} are compared under complete linkage in 1D. What distance is used?
打开 →题目4287 · 机器学习
Why k-Means Struggles on Two Moons
Why can k-means behave poorly when one feature has a much larger scale than the others?
打开 →题目4286 · 机器学习
Why Scaling Matters for k-Means
You expect non-convex moon-shaped clusters plus some noise points. Would you try k-means or DBSCAN first, and why?
打开 →模块2.6.4 · 数学与统计能力 · 机器学习理论
无监督学习与强化学习
machine-learning · unsupervised-learning · clustering · k-means · gaussian-mixture-model · em-algorithm · kernel-density-estimation · regime-detection
打开 →课程无监督学习与强化学习 · 机器学习理论
聚类与密度估计
Hook:5 年沪深300 日收益,你能不能贴出「风险开关」标签 上海某私募的初级量化研究员张昊把过去 5 年的沪深300 日收益拉成一张表——列是 20 日已实现波动率(realized volatility)、申万一级行业截面收益离散度(cross sectional dispersion)、60 日市值加权平均成对相关,1,200 多个交易日。组长甩话...
打开 →课程无监督学习与强化学习 · 机器学习理论
强化学习基础:马尔可夫决策过程与贝尔曼方程
强化学习基础:马尔可夫决策过程与贝尔曼方程 Hook:30 分钟,100 张 IF 主力合约 周三 14:30,你在一家中型私募负责股指期货 CTA 产品。组合调仓信号刚切换,系统要在收盘前 30 分钟里把 CFFEX 的 IF2406 主力合约(沪深300 股指期货)多头持仓从 100 张减到 0。一次甩出 100 张市价单,冲击成本(market imp...
打开 →课程无监督学习与强化学习 · 机器学习理论
策略梯度与深度强化学习
策略梯度与深度强化学习 开篇场景：表格放不下的盘口 周三盘后，上海一家头部 私募 的初级量化把成果摊给组长：CFFEX 上 沪深300 股指期货 日内大单切片，建成 144 个离散状态的 MDP，跑通了表格 Q 学习，比 TWAP 省了约 2bp 的 实施差额（implementation shortfall）。组长翻两页就皱眉：「线上要吃 5 档盘口 + ...
打开 →课程无监督学习与强化学习 · 机器学习理论
降维与表示学习
Hook：没有 Barra 许可证的统计风险模型 周二早上，某中型多空对冲私募给初级量化研究员的任务：周五交一套「统计风险模型」——把沪深300 成分股最近 1000 个交易日的日度收益拆成几个共同因子加特异噪声，做成数据驱动的因子模型（factor model）。没有 Barra 模型（Barra model）授权，基本面数据要月底涨价，只有 1000×3...
打开 →题目4283 · 机器学习
Average Linkage Distance 3
A 2D k-means run has centroids at (0,0) and (4,0). For point x=(1,2), which centroid is closer in the assignment step?
打开 →题目5039 · 机器学习
EM Mixture Diagnostic 24
Why can k-means and a Gaussian mixture with shared spherical covariances give similar clusters, yet still disagree on borderline points?
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