Top "Dimensionality-reduction" questions

In machine learning and statistics, dimensionality reduction or dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and feature extraction.

Plot PCA loadings and loading in biplot in sklearn (like R's autoplot)

I saw this tutorial in R w/ autoplot. They plotted the loadings and loading labels: autoplot(prcomp(df), data = iris, …

python scikit-learn pca dimensionality-reduction biplot
what is dimensionality in word embeddings?

I want to understand what is meant by "dimensionality" in word embeddings. When I embed a word in the form …

nlp terminology dimensionality-reduction word-embedding
LDA ignoring n_components?

When I am trying to work with LDA from Scikit-Learn, it keeps only giving me one component, even though I …

python scikit-learn dimensionality-reduction
How to efficiently find k-nearest neighbours in high-dimensional data?

So I have about 16,000 75-dimensional data points, and for each point I want to find its k nearest neighbours (using …

algorithm data-structures computational-geometry nearest-neighbor dimensionality-reduction
PCA for dimensionality reduction before Random Forest

I am working on binary class random forest with approximately 4500 variables. Many of these variables are highly correlated and some …

pca random-forest dimensionality-reduction