Refer to code
..
from sklearn.manifold import TSNE
from keras.datasets import mnist
from sklearn.datasets import load_iris
from numpy import reshape
import seaborn as sns
import pandas as pd
iris = load_iris()
x = iris.data
y = iris.target
# from sklearn.utils import shuffle
# x, y = shuffle(x, y)
tsne = TSNE(n_components=2, verbose=1, random_state=123)
z = tsne.fit_transform(x)
df = pd.DataFrame()
df["y"] = y
df["comp-1"] = z[:,0]
df["comp-2"] = z[:,1]
sns.scatterplot(x="comp-1", y="comp-2", hue=df.y.tolist(),
palette=sns.color_palette("hls", 3),
data=df).set(title="Iris data T-SNE projection")
..
output
