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David's Perspective

Sharing my idea about business analytics, machine learning, and data science.

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標籤:Machine Learning

截圖 2020-07-31 上午12.48.45

Cross Validation 得到「測試誤差」的信賴區間與假設檢定

交叉驗證 (cross validati … More

confidence interval, cross validation, Machine Learning
截圖 2020-04-27 上午12.11.16

一般化隨機森林 (Generalized Random Forest)

今天想跟大家介紹的論文是 2019 年刊 … More

Causal Inference, Generalized Random Forest, Local Estimation, Machine Learning
螢幕快照 2020-01-29 下午7。55。07

改善客戶流失管理:以「增益」為基礎的定位策略

今年我們公司與清大的 Business … More

AB Test, Causal Inference, Customer Churn Management, Machine Learning, Uplift Model
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(2018) 資料科學線上課程總彙 – 機器學習篇

最近有位讀者透過粉專私訊詢問: 讀了一篇 … More

Data Science, Deep Learning, Machine Learning, Reinforcement Learning
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使用 LIME 解釋複雜的分類模型

許多領域問題除了準確的預測外,更需要了解 … More

Classification, Explainable AI, Lime, Local Interpretable Model-Agnostic Explanations, Machine Learning
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你可能不知道的邏輯迴歸 (Logistic Regression)

邏輯迴歸通常是在學分類問題 (class … More

Classification, Data Mining, Logistic Regression, Machine Learning
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譜分群 (Spectral Clustering) ─ 運用圖論 (Graph Theory) 進行分群

分群 (Clustering) 是非監督 … More

Graph Laplacian, Machine Learning, Spectral Clustering
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機器學習中的貝氏定理:生成模型 (Generative Model) 與判別模型 (Discriminative Model)

GAN (Generative Adve … More

Bayesian Statistics, Discriminative Model, Generative Model, Machine Learning
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