Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…applied-math-coding.medium.com This story is part of my Data Science series. In my previous story (see here), I have provided an example implementation for a random forest based on a classification problem stemming from this set of data.

Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…applied-math-coding.medium.com This story is part of my Data Science series. Random forests do come in many variations. The common idea is instead building a single tree model, one trains an ensemble of tree model where each has slightly different input parameters. These input parameters for instance could be a random-selected subset…

Join Medium with my referral link — applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…applied-math-coding.medium.com This story is part of my Data Science series. Typically when we create a classification or regression model we try to keep it as simple as possible. Simplification can be reached in many ways, and one is to reduce the considered features to a small as possible subset.

Join Medium with my referral link — applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…applied-math-coding.medium.com This story is part of my Data Science series. In our previous story (see here) we have looked at the theory behind the QR-algorithm that aims to find all eigenvector/eigenvalue pairs of a matrix. Now we consider a possible implementation in Rust.

Join Medium with my referral link — applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…applied-math-coding.medium.com This story is part of my Data Science series. After having seen various methods about eigenvector computation, i.e. power method and deflation method, we now come to one that is hard to surpass in terms of ingenuity.

Join Medium with my referral link — applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…applied-math-coding.medium.com This story is part of my Data Science series. In our previous story (see here), we have looked at a procedure to compute the in absolute terms highest eigenvalue of a finite dimensional endomorphism — a (n,n)-matrix. For applications like the principle component analysis we need all eigenvalues, or at…

Join Medium with my referral link — applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…applied-math-coding.medium.com This story is part of my Data Science series. To exactly compute the eigenvalue/eigenvectors pairs, there exists several methods. One of this is the so called power method at which theory and implementation this article is devoted.

Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…applied-math-coding.medium.com This story is part of my Data Science series. In this article we restrict our attention to the problem of finding eigenvector/eigenvalue pairs for a finite dimensional linear operator. In many applications of machine learning one is interested in those eigenvectors that belong to the highest eigenvalues in absolute value…

Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…medium.com This story is part of my Data Science series. Many data sets come with an enormous amount of feature variables. On the one hand this is positive because it yields a large amount of information that we can incorporate in a machine learning algorithm, but on the other hand it…