TheoreticFoundationofPredictiveAnalytics.pdf
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甲基蓝
2024-04-19
Model
Inter
pret
ation
vs.
Data
Probability
Variables
机器
Ran
669.6 KB
Theoretic Foundation of Predictive Data Analytics
By Jun Huan
July, 2015
Contents
Preface ii
I Basics 1
1 Introduction 2
1.1 A Big Picture of Predictive Data Analytics . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Data, Model, and Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Uncertainty, Consistency, Loss, and Risk . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.4 Overfitting and Its Prevention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.5 Bayesian vs. Frequentist Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.6 Methematical Treatment of Random Variable . . . . . . . . . . . . . . . . . . . . . . 3
1.7 Model Interpretation vs. Model Evaluation . . . . . . . . . . . . . . . . . . . . . . . 3
2 Probability Theory and Laws of Large Numbers 5
2.1 Axioms of Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 Random Variables . . . . . . . . . . . .
Model/Inter/pret/ation/vs./Data/Probability/Variables/机器/Ran/
Model/Inter/pret/ation/vs./Data/Probability/Variables/机器/Ran/
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