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.
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 biplotI want to understand what is meant by "dimensionality" in word embeddings. When I embed a word in the form …
nlp terminology dimensionality-reduction word-embeddingWhen I am trying to work with LDA from Scikit-Learn, it keeps only giving me one component, even though I …
python scikit-learn dimensionality-reductionSo 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-reductionI 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