Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Detecting QTL Hotspots in Sparse Regression Models
Graph Chatbot
Related lectures (34)
Regularization in Machine Learning
Log in to Mediaspace to watch this video
Introduces regularization techniques to prevent overfitting in machine learning models.
Regression Methods: Model Building and Inference
Log in to Mediaspace to watch this video
Covers Inference, Model Building, Variable Selection, Robustness, Regularised Regression, Mixed Models, and Regression Methods.
Supervised Learning: Regression Methods
Log in to Mediaspace to watch this video
Explores supervised learning with a focus on regression methods, including model fitting, regularization, model selection, and performance evaluation.
Statistical Inference: Linear Models
Log in to Mediaspace to watch this video
Explores statistical inference for linear models, covering model fitting, parameter estimation, and variance decomposition.
Regression Methods: Model Building and Inference
Log in to Mediaspace to watch this video
Covers analysis of variance, model building, variable selection, and function estimation in regression methods.
Basics of Linear Regression
Log in to Mediaspace to watch this video
Covers the basics of linear regression, including OLS estimators, hypothesis testing, and confidence intervals.
Basics of linear regression model
Log in to Mediaspace to watch this video
Covers the basics of linear regression, OLS method, predicted values, residuals, matrix notation, goodness-of-fit, hypothesis testing, and confidence intervals.
Regularization Techniques
Log in to Mediaspace to watch this video
Explores regularization in linear models, including Ridge Regression and the Lasso, analytical solutions, and polynomial ridge regression.
Modern Regression: Spring Barley Data
Log in to Mediaspace to watch this video
Covers iterative weighted least squares, Poisson regression, and Bayesian analysis of spring barley data using mixed models.
Probability and Statistics: Basics and Applications
Log in to Mediaspace to watch this video
Covers fundamental concepts of probability and statistics, focusing on data analysis, graphical representation, and practical applications.
Regression Methods: Model Building and Diagnostics
Log in to Mediaspace to watch this video
Explores regression methods, covering model building, diagnostics, inference, and analysis of variance.
Generalized Linear Models: A Brief Review
Log in to Mediaspace to watch this video
Provides an overview of Generalized Linear Models, focusing on logistic and Poisson regression models, and their implementation in R.
Probability Model Construction
Log in to Mediaspace to watch this video
Explores constructing a probability model, random sampling, variance calculation, and allocation optimization in experiments.
Modern Regression: Inference and Models
Log in to Mediaspace to watch this video
Covers iterative weighted least squares, model checking, and generalized linear models in regression analysis.
Previous
Page 2 of 2
Next