# Questions tagged [linear-algebra]

A field of mathematics concerned with the study of finite dimensional vector spaces, including matrices and their manipulation, which are important in statistics.

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### Possible flaw in the MDS method for dimensionality reduction

The MDS (multidimensional scaling) method is used to solve the problem of dimensionality reduction. Basically, it does the following: given $n$ points $x_1,\cdots,x_n\in\mathbb R^d$, try to find a ...
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### Best linear algebra library for c++?

I have been trying to find the substitute of numpy and perform some linear algebra using c++ and here's a list of libraries I have encountered: Eigen Armadillo Dlib GNU Scientific library Please ...
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### Deriving vectorized form of linear regression

We first have the weights of a D dimensional vector $w$ and a D dimensional predictor vector $x$, which are all indexed by $j$. There are $N$ observations, all D dimensional. $t$ is our targets, i.e, ...
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### How does SVD actually provide the recommendations? I seem to get conflicting answers

I am reading a text book that basically says the following: Given a matrix A where A is USERS x ITEMS we can use SVD to decompose the matrix into: $$A = U \times \Sigma \times V^T$$ Then we can take ...
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### Hypothesis vs Hyperplane in Machine Learning

I am finding it hard to understand the clear difference between Hypothesis and Hyperplane. I know that Hypothesis is a candidate model that maps inputs to outputs after training . And , Hyperplane is ...
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### Intuition behind understanding eigenvectors and Machine Learning

I am struggling to understand linear algebra application in machine learning, and I am not able to answer the following question. Is the model learned in Machine Learning the eigenvector of the ...
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### Why transpose of independent feature matrix is necessary in case of linear regression?

I can follow classical linear regression steps: $Xw=y$ $X^{-1}Xw=X^{-1}y$ $Iw=X^{-1}y$ $w=X^{-1}y$ However, on implementing in Python, I see that instead of simply using ...
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### Linear regression with a fixed intercept and everything is in log

I have a set of values for a surface (in pixels) that becomes bigger over time (exponentially). The surface consists of cells that divide over time. After doing some modelling, I came up with the ...
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### What does sparsely compute mean?

I heard someone say a neural network needs to sparsely compute the output. I get what compute means, I get what a sparse matrix is, but what does sparsely compute mean?