tsne-embedding-example.md

TSNe embedding example

import numpy as np
from sklearn import manifold

X = np.array([[0, 0, 0], [0, 1, 1], [1, 0, 1], [1, 1, 1]])
Xe = manifold.TSNE(n_components=2, learning_rate='auto', init='random').fit_transform(X)

• import numpy - import lib:Numpy module
• from sklearn import - import module from lib:scikit-learn
• .TSNE( - creates T-distributed Stochastic Neighbor Embedding model
• n_components=2 - reduce dataset to 2 features
• .fit_transform( - train and transform given dataset
• Xe - will contain embedded dataset

Example:

import numpy as np
from sklearn.manifold import TSNE

X = np.array([[0, 0, 0], [0, 1, 1], [1, 0, 1], [1, 1, 1]])
print(X.shape)

Xe = TSNE(n_components=2, learning_rate='auto', init='random').fit_transform(X)
print(Xe.shape)

(4, 3)
(4, 2)