# Reduce dimensions

Model / reduce

PCA, SVD, UMAP, t-SNE, other dimensionality reduction

Page: <https://meridian.online/operations/reduce-dimensions>

## Status

Not built yet.

arcform does not do this yet. [Its place on the roadmap](https://meridian.online/roadmap#reduce-dimensions)

arcform has `umap_project` for UMAP.

## Variants

- Factorise a matrix into low-rank parts: Split a matrix into two or three low-rank factor matrices, as SVD and non-negative matrix factorisation do.
- Project rows onto fewer dimensions: Replace many numeric columns with a few components or coordinates for each row, as PCA, MDS or ICA do.

## What other tools call it

Meridian's classification; an independent blind rating agreed on 86.2% of 312 rows (exact class, version 2).

- Alteryx Designer: [`Multidimensional Scaling`](https://help.alteryx.com/current/en/designer/tools/predictive-grouping/multidimensional-scaling-tool.html) (read 2026-09-27)
- Alteryx Designer: [`Principal Components`](https://help.alteryx.com/current/en/designer/tools/predictive-grouping/principal-components-tool.html) (read 2026-09-27)
- KNIME Analytics Platform: [`KNIME Nodes for Statistics and Social Science (extension)`](https://api.hub.knime.com/extensions/uni.bocconi.features.social-science) (read 2026-09-27)
- KNIME Analytics Platform: [`Linear Discriminant Analysis`](https://api.hub.knime.com/nodes/*ibfEoz796QwX_D58?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`Linear Discriminant Analysis Apply`](https://api.hub.knime.com/nodes/*yXg3V3qqr5tNisPz?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`Linear Discriminant Analysis Compute`](https://api.hub.knime.com/nodes/*RT67ZpXySYm9FBWc?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`Linear Discriminant Analysis Inversion`](https://api.hub.knime.com/nodes/*n0KS_t4gGEs6daD6?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`MDS`](https://api.hub.knime.com/nodes/*SCgPuzvfM-9t325D?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`MDS Projection`](https://api.hub.knime.com/nodes/*EeJsApVFGjfKslVY?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`PCA`](https://api.hub.knime.com/nodes/*-BB0l1REE9I_B16p?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`PCA Apply`](https://api.hub.knime.com/nodes/*JhkFvp5w8i1VQ7Wf?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`PCA Compute`](https://api.hub.knime.com/nodes/*KrQKjrbm1MZhJvTT?details=full) (read 2026-09-27)
- KNIME Analytics Platform: [`PCA Inversion`](https://api.hub.knime.com/nodes/*0z1rRuudqtL_QKdI?details=full) (read 2026-09-27)
- mlpack: [`AMF`](https://www.mlpack.org/doc/user/transformations.html) (read 2026-09-27)
- mlpack: [`LocalCoordinateCoding`](https://www.mlpack.org/doc/user/transformations.html) (read 2026-09-27)
- mlpack: [`NMF`](https://www.mlpack.org/doc/user/transformations.html) (read 2026-09-27)
- mlpack: [`PCA`](https://www.mlpack.org/doc/user/transformations.html) (read 2026-09-27)
- mlpack: [`RADICAL`](https://www.mlpack.org/doc/user/transformations.html) (read 2026-09-27)
- mlpack: [`SparseCoding`](https://www.mlpack.org/doc/user/transformations.html) (read 2026-09-27)
- mlpack: [`bias_svd`](https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods) (read 2026-09-27)
- mlpack: [`block_krylov_svd`](https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods) (read 2026-09-27)
- mlpack: [`mlpack_kernel_pca`](https://www.mlpack.org/doc/user/bindings/cli.html) (read 2026-09-27)
- mlpack: [`nystroem_method`](https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods) (read 2026-09-27)
- mlpack: [`quic_svd`](https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods) (read 2026-09-27)
- mlpack: [`randomized_svd`](https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods) (read 2026-09-27)
- mlpack: [`regularized_svd`](https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods) (read 2026-09-27)
- mlpack: [`sparse_autoencoder`](https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods) (read 2026-09-27)
- mlpack: [`svdplusplus`](https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods) (read 2026-09-27)
- RapidMiner Studio: [`Independent Component Analysis`](https://docs.rapidminer.com/latest/studio/operators/cleansing/dimensionality_reduction/independent_component_analysis.html) (read 2026-09-27)
- RapidMiner Studio: [`Principal Component Analysis`](https://docs.rapidminer.com/latest/studio/operators/cleansing/dimensionality_reduction/principal_component_analysis.html) (read 2026-09-27)
- RapidMiner Studio: [`Principal Component Analysis (Kernel)`](https://docs.rapidminer.com/latest/studio/operators/cleansing/dimensionality_reduction/principal_component_analysis_kernel.html) (read 2026-09-27)
- RapidMiner Studio: [`Self-Organizing Map`](https://docs.rapidminer.com/latest/studio/operators/cleansing/dimensionality_reduction/self_organizing_map.html) (read 2026-09-27)
- RapidMiner Studio: [`Singular Value Decomposition`](https://docs.rapidminer.com/latest/studio/operators/cleansing/dimensionality_reduction/singular_value_decomposition.html) (read 2026-09-27)