t-Stochastic Neighbor Embedding Example

t-sne.py

Python
from sklearn import datasets
import seaborn as sn
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
 
#import the digits dataset
digits = datasets.load_digits()
 
X = digits.data
y = digits.target
 
tsne = TSNE(n_components=2, random_state=0)
tsne_data = tsne.fit_transform(X)
 
#creating a new dataframe for plotting
tsne_data = np.vstack((tsne_data.T, y)).T
tsne_df = pd.DataFrame(data=tsne_data, columns=("Dim_1", "Dim_2", "label"))
 
#Plotting the result
sn.FacetGrid(tsne_df, hue="label", size=6).map(plt.scatter, 'Dim_1', 'Dim_2').add_legend()
plt.show()
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from sklearn import datasets
import seaborn as sn
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
 
#import the digits dataset
digits = datasets.load_digits()
 
X = digits.data
y = digits.target
 
tsne = TSNE(n_components=2, random_state=0)
tsne_data = tsne.fit_transform(X)
 
#creating a new dataframe for plotting
tsne_data = np.vstack((tsne_data.T, y)).T
tsne_df = pd.DataFrame(data=tsne_data, columns=("Dim_1", "Dim_2", "label"))
 
#Plotting the result
sn.FacetGrid(tsne_df, hue="label", size=6).map(plt.scatter, 'Dim_1', 'Dim_2').add_legend()
plt.show()