Generate a multi-dimensional star tree data that contain
n_samples
data points and fit a star tree with n_arms
arms.
generate_n_arms_star_data(n_features, n_samples, n_arms, fatness)
n_features | The number of features (dimensions) to be generated. |
---|---|
n_samples | The number of samples to be generated. |
n_arms | The number of arms to be generated. |
fatness | How fat from the based star tree. |
A generated martix
. The rows and columns correspond to
samples and features.
# Generate a 100-dimensional star tree data that contain 500 data points # and fit a star tree with 3 arms. The generated data are a bit noisy but # tree-like. star100.tree_like <- treefit::generate_n_arms_star_data(100, 500, 3, 0.1) # Reduce dimension to visualize. star3.tree_like = prcomp(star100.tree_like, rank.=3)$x plotly::plot_ly(data.frame(star3.tree_like), x=~PC1, y=~PC2, z=~PC3, type="scatter3d", mode="markers", marker=list(size=1))