# Questions tagged [sparse]

A sparse matrix is a matrix where many of the elements are zeros. The tag can also be used for sparsity in other contexts, such as regression models with sparsity, or the "bet on sparsity"-principle.

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### MAE to find tuning parameter for lasso logistic regression

I have a classification problem. The actual outcomes are binary (0 or 1), but I want to predict probabilities, rather than predicting simply 0 or 1. I also want something with feature selection, since ...
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1 vote
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### What are the modes of a dictionary / transform basis?

So, I'm reading Steven Brunton's book, "Data Driven Science & Engineering", and I'm trying to understand what he means by mode in this following excerpt: Most natural signals, such as ...
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### How to measure distances between sparse vectors when the dimensions are not independent?

I am searching for a similarity metric between vectors that are sparse-ish, but most distance metrics treat each dimension as independent and this can create problems when comparing distances between ...
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### How adding sparsity term in loss function of sparse autoencoder in-actives the hidden node?

I am working on a Sparse Autoencoder but Andrew NG's notes are hard to understand. My question is about the following equation: Loss Function. image In sparse autoencoder, the goal is to inactive some ...
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### Why lasso cannot be arbitrarily applied?

Consider any log likelihood function $f(\theta|x)$ where $x$ is data. I can consider $f(\theta|x)+\lambda||\theta||_1$ where $||\theta||_1$ is the standard $L_1$ norm. It seems that I cannot apply ...
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1 vote
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### How to solve the problem of having sparse data that would become too small when aggregated?

I have a dataset that provides the count of cyber incidents since 2011 for different countries and different attack types, and I want to use this data in a machine learning model to predict future ...
290 views

### Is it wrong to run a Random Forest on high-dimensional, sparse, and unbalanced data?

I am learning about random forests, and I have been testing using R. I have doubts about whether I am doing something wrong given that my data are: sparse, high-dimensional, and unbalanced. Trying to ...
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### Working with sparse data in numpy and sklearn [closed]

I have a time series dataset geenrated from some electrophysiological data. I have a frequncy dataset and the matrix is quite sparse but huge, like it contains 0.005 s time bins for 2000+ neurons ...
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