1. Build a custom cross-validation function for a machine learning model in R, ensuring that each fold contains a representative distribution of the target variable. 2. Create an optimization algorithm in R to find the minimum of a complex, non-convex function with multiple parameters. 3. Given a time series dataset, implement a seasonal decomposition using LOESS (STL) and explain how each component contributes to the overall pattern.
1. Build a custom cross-validation function for a machine learning model in R, ensuring that each fold contains a representative distribution of the target variable. 2. Create an optimization algorithm in R to find the minimum of a complex, non-convex function with multiple parameters. 3. Given a time series dataset, implement a seasonal decomposition using LOESS (STL) and explain how each component contributes to the overall pattern.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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