# Articles — Math

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Methods to prevent overfitting and solve ill-posed problems in statistics: Ridge Regression and LASSO
Linear regression is one of the most widely used statistical methods available today. It is used by data analysts and students in almost every discipline. However, for the standard ordinary least squares method, there are several strong assumptions made about data that is often not true in real world data sets. This can cause numerous problems in the least squares model. One of the most common issues is a model overfitting the data. Ridge Regression and LASSO are two methods used to create a better and more accurate model. I will discuss how overfitting arises in least squares models and the reasoning for using Ridge Regression and LASSO include analysis of real world example data and compare these methods with OLS and each other to further infer the benefits and drawbacks of each method.
Chris Van Dusen
SVD-разложение и его практические приложения (SVD-decomposition and its practical applications)
SVD-разложение и его практические приложения с исходным кодом на языке Matlab. (SVD - decomposition and its practical applications with source code in the language Matlab.
Eugene Kolesnikov
Assignment One
Modern Algebra HW
Kenneth Iannello
My Final Proof Journal
-------------------------------------------------------------- This is all preamble stuff that you don't have to worry about. Head down to where it says "Start here" --------------------------------------------------------------
Chesyti Brown
ستة تعاريف للدالة الأسية للأساس $e$
Compiler à l'aide de XeLaTeX %%
Noureddine
Abstract Algebra Lecture Notes
This is a set of notes for the first two chapters of an Abstract Algebra course, following the Hungerford textbook table of contents. One notable feature is the use of a couple of commands that allow one to show only definitions, or only the examples, etc., and another command that allows one to format examples for making handouts.
educkworth
Drawing Lines
Notes on Machine Learning.
Raghav Saboo