Skip to main content

calculate condition number and determinant in R and python


Introduction:


If you are working on machine learning, more than often, you will need to perform different types of matrix manipulations in r/python. I will mention some of such manipulations and regarding functions to use in r and python.

condition number finding:

condition number is generally used to find the stability as well non-singularity of a matrix. It is defined to be the ratio of absolute value of highest singular value and smallest singular value ( in terms of mod value). If a matrix has condition number more than 1000, then it is generally considered to be a unstable matrix.

For finding condition number of a matrix in r, we have to use the kappa() function. For normally using kappa, you need to use two parameters. First input to kappa has to be the matrix. The second one is exact parameter. This exact is set to be FALSE in general. In this setting, a cheap (computationally) approximation of condition number is obtained and provided. If you set kappa to be TRUE, then the method uses SVD and provides the exact value.

so the usecase is condition_number = kappa( matrix, exact = FALSE)

In case of python, you can import cond from numpy.linalg, i.e. the linear algebra library. cond takes the matrix as parameter and calculates the condition number.

determinant:

For determinant, it is amazing that both numpy.linalg and R has same function, called det(). det(), in both cases takes the matrix as parameter and provides the determinant value.
Labels:

Comments

Post a Comment

Popular posts from this blog

20 Must-Know Math Puzzles for Data Science Interviews: Test Your Problem-Solving Skills

Introduction:   When preparing for a data science interview, brushing up on your coding and statistical knowledge is crucial—but math puzzles also play a significant role. Many interviewers use puzzles to assess how candidates approach complex problems, test their logical reasoning, and gauge their problem-solving efficiency. These puzzles are often designed to test not only your knowledge of math but also your ability to think critically and creatively. Here, we've compiled 20 challenging yet exciting math puzzles to help you prepare for data science interviews. We’ll walk you through each puzzle, followed by an explanation of the solution. 1. The Missing Dollar Puzzle Puzzle: Three friends check into a hotel room that costs $30. They each contribute $10. Later, the hotel realizes there was an error and the room actually costs $25. The hotel gives $5 back to the bellboy to return to the friends, but the bellboy, being dishonest, pockets $2 and gives $1 back to each friend. No...
Post a Comment
Read more

Deep Learning by Ian GoodFellow, Yoshua Bengio and Aaron courville Review

History: I have been reading deep learning topics from a number of resources like machine learning mastery by Jason Brawlee, Analyticsvidhya, and other blog resources. But the problem has stayed, the problem of inconsistency in the knowledge. Therefore, I have decided to now sit down, and go through a deep learning book thoroughly. And what better name for deep learning other than Ian Goodfellow! So I have found this book named Deep Learning by Ian Goodfellow. Introduction: Plan for this post is reviewing and rewriting the topics from the book, in simpler language and for sharing the pieces of knowledge with my readers. I will update this post continuously as I proceed with the reading also. So ideally this post is broadly about basic to advanced deep learning material discussion. Sponsored Ads Learn deep learning in python with Udemy   Different parts of the book and purpose of them: This book has three parts,which talks about (1) applied mathematics and machine learni...
Post a Comment
Read more

Pyarabic: python package for Arabic language

 Introduction:  In languages which are non-english and non-european as well, NLP work has progressed slowly in the last few decades because of the lesser number of scholars working on them as well as a lack of global interest in them. But now the time has changed and people from all over the world are collaborating on these lesser explored libraries and they are building resources for working on these languages with the same ease with that of english.  Pyarabic is a package created from such a similar effort which deals with the intricate details of the arabic language and helps processing all kinds of arabic texts. While trying to learn it, being from a non-arab background, I couldn't read lots of parts of the main readthedocs site and had to work my around it. So in this blog post, I will summarize my learnings in english language, so that you can learn it and use the package with much more ease than me. [Credit where credit is due: this article heavily uses the ac...
Post a Comment
Read more