TSNe embedding example #1904

Onelinerhub · Dec 16, 2022 · f4da97c · f4da97c
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 # TSNe embedding example
 
 ```python
 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](https://onelinerhub.com/python-numpy/how-to-install-python-numpy-lib) module
 - `from sklearn import` - import module from [lib:scikit-learn](https://onelinerhub.com/python-scikit-learn/how-to-install-scikit-learn-using-pip)
 - `.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
 
 group: tsne
 
 ## Example: 
 ```python
 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)
 
 ```