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1
Intro
2
Predictive Distribution
3
Model Comparison
4
Model Parameters
5
Selection Procedure
6
Linear Models
7
Binary Classification
8
Maximum Molecular Estimation
9
Logistic Regression
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Learn about predictive distribution modeling, model comparison techniques, and parameter selection in this graduate-level data science lecture. Explore essential concepts including linear models, binary classification methods, maximum molecular estimation, and logistic regression fundamentals. Gain deep insights into model selection procedures and statistical approaches used in modern data analysis and machine learning applications.

Predictive Distribution and Model Comparison in Linear Models - Lecture 12

UofU Data Science
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