# Questions tagged [high-dimensional]

Pertains to a large number of features or dimensions (variables) for data. (For a large number of data points, use the tag [large-data]; if the issue is a larger number of variables than data, use the [underdetermined] tag.)

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### Comparing scree plots or explained variance of two groups with different number of features after PCA

I want to define the dimensionality of a group as the number of PC features that can explain 80% of the variance in the group dataset. This intuition seems to work for a single group, however, if I ...
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### Tensorization of entropy: confusion regarding conditional entropy

I'm reading High-Dimensional Statistics by Wainright. In the book, entropy for random variable $Z \geq 0$ is defined as $H(Z) = E[Z \log Z]- E[Z] \log E[Z]$. My understanding is that $H(Z)$ is a ...
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### Seeking recommendations for feature selection methods before applying a random forest model to high-dimensional data

I'm seeking recommendations for feature selection methods before applying a random forest model to high-dimensional data, specifically with over 60,000 features and only 1,000 samples. My concern is ...
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### Do neural networks work with high-dimensional small sample data?

Are neural networks used for the classification of high-dimensional small sample data like gene microarray data, where the dimension may be on the order of 1000 features per sample with around 100 ...
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### Clustering or factor analysis for dimensionality reduction in multivariate linear regression

I have dataset describing aggregated purchases from multiple brands. It contains variables: Brand (ordinal) Promotion (ordinal) Sales (numeric) I need to use linear regression to describe the effect ...
Suppose the objective function to be minimized is $$F(\theta) = \|y - X \theta\|_2^2 + \sum_{i=1}^p \lambda_i |\theta_i|$$ where $\theta$ is the independent variable which is feasible in $\mathbb{R}^p$...