add tsne

train/tsne.py

@@ -0,0 +1,18 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from sklearn import datasets
+from sklearn.manifold import TSNE
+
+iris = datasets.load_iris()
+X = iris.data
+y = iris.target
+
+# t-SNE with two components (2D visualization)
+tsne = TSNE(n_components=2, random_state=42)
+X_tsne = tsne.fit_transform(X)
+
+plt.scatter(X_tsne[:, 0], X_tsne[:, 1], c=y, cmap=plt.cm.Set1, edgecolor='k')
+plt.title("t-SNE Visualization of Iris Dataset")
+plt.xlabel("t-SNE Component 1")
+plt.ylabel("t-SNE Component 2")
+plt.show()