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