eGTM: GTM transformer

Run GTM

eGTM is a sklearn-compatible GTM transformer. Similarly to PCA or t-SNE, eGTM reduces the dimensionality from n_dimensions to 2 dimensions. To generate mean GTM 2D projections:

from ugtm import eGTM
import numpy as np

X_train = np.random.randn(100, 50)
X_test = np.random.randn(50, 50)

# Fit GTM on X_train and get 2D projections for X_test
transformed = eGTM().fit(X_train).transform(X_test)

The default output of eGTM.transform is the mean GTM projection. For other data representations (modes, responsibilities), see transform().

Visualize projection

Visualization demo using altair https://altair-viz.github.io:

from ugtm import eGTM
import numpy as np
import altair as alt
import pandas as pd

X_train = np.random.randn(100, 50)
X_test = np.random.randn(50, 50)

transformed = eGTM().fit(X_train).transform(X_test)

df = pd.DataFrame(transformed, columns=["x1", "x2"])
alt.Chart(df).mark_point().encode(
x='x1',y='x2',
tooltip=["x1", "x2"]
).properties(title="GTM projection of X_test").interactive()