Local_TSA: Local Tangent Space Alignment
In kcf-jackson/maniTools: Manifold learning in R

Description Usage Arguments Details Value References Examples

Local Tangent Space Alignment

1	Local_TSA(X, k, d)

`X`	N x D matrix (N samples, D features).
`k`	integer; Number of nearest neighbor.
`d`	integer; The target dimension.

Matlab codes were written by Zhenyue Zhang & Hongyuan Zha (2004) and extracted from Todd Wittman's MANI: Manifold Learning Toolkit.

N x d matrix; the projected data.

Zhang, Z., & Zha, H. (2004). Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment. SIAM Journal on Scientific Computing, 26(1), 313-338.

MANI: Manifold Learning Toolkit - http://macs.citadel.edu/wittman/research.html

#Simulate data
sim_data <- swiss_roll(N = 600)
library(plotly)
p1 <- plotly_3D(sim_data); p1
LTSA_data <- Local_TSA(sim_data$data, k = 8, d = 2)
p2 <- plotly_2D(LTSA_data, color = sim_data$colors); p2