the art of data science
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The Art of Data Science(Chapter7. Formal Modeling)
Produced by Lee Tae Young
Formal Modeling
Formal Modeling
Setting expectations.
Collecting Information.
Revising expectations.
Primary model Secondary models
Associational AnalysesOutcome. Key predictor. Potential confounders.
EX) Online advertising campaignExpectationsSetting Expectations.More realistic dataEvaluation
1. Effect size.2. Plausibility. (타당성 )3. Parsimony. (간결 )
Prediction Analysesclassification problem
Expectations
Real world data
Evaluation1. Prediction quality.2. Model tuning.
3. Availability of Other Data.
Summary• Formal Modeling : 분석의 기본 Frame 제공– 기본 : 엄격함 , 시험하기 위한 도구
• Prediction 의 근간이 됨
Communication
Routine communication
The Audience(대상 )
Content(내용 )Style
Attitude
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