YoVDO

Dual-SPLS - A Versatile Approach Improving PLS with Lasso Shrinkage

Offered By: Chemometrics & Machine Learning in Copenhagen via YouTube

Tags

High-Dimensional Data Analysis Courses Analytical Chemistry Courses Predictive Modeling Courses Dimension Reduction Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a 42-minute webinar on dual-sPLS, a novel algorithm that enhances Partial Least Squares (PLS) with Lasso shrinkage. Presented by Louna Alsouki from the University of Claude-Bernard and University of Saint Joseph de Beyrouth, learn how this versatile approach tackles high-dimensional problems in analytical chemistry. Discover the integration of projection methods and variable selection algorithms to achieve more accurate and interpretable results. Understand the mechanics of sparse PLS and how dual-SPLS improves upon it, offering a sparser data representation while maintaining predictive accuracy. Delve into the concept of dual norms and their application in the algorithm, including the handling of multiple predictor sets related to a single response variable. Gain insights into how adaptive penalization and various norm types contribute to solving complex analytical chemistry challenges. Access accompanying slides for a comprehensive understanding of this innovative technique.

Syllabus

Monday Webinar. Dual-sPLS: a versatile approach improving PLS with Lasso shrinkage


Taught by

Chemometrics & Machine Learning in Copenhagen

Tags

Related Courses

Applied Multivariate Analysis
University of Calcutta via Swayam
Big Data Analytics
Queensland University of Technology via FutureLearn
How to analyze a microbiome
KU Leuven University via edX
Unsupervised Learning in Python
DataCamp
Linear Algebra for Data Science in R
DataCamp