TSNE-embedding

tsne = TSNE(n_components=2, random_state=0,verbose=1,perplexity=50,init='pca')
X_2d = tsne.fit_transform(X_t)

target_ids = [0,1]
y_t=y_t.astype('int')

plt.figure(figsize=(10,6))
colors = 'r', 'g'
target_names=['Reject','Accept']
for i, c, label in zip(target_ids, colors, target_names):
    plt.scatter(X_2d[y_t[:,-1] == i,0], X_2d[y_t[:,-1] == i,1], c=c, label=label)
plt.axis('off')

plt.legend()