Added Preview of Dataset to model.

app.py

@@ -163,6 +163,54 @@ def plot_on_dataset(X, y, models, name):
     
     return plt
 
+
+def plot_example(dataset):
+    if dataset == 0: # Iris
+        fig = plt.figure()
+        iris = datasets.load_iris()
+        col_1 = iris.data[:, 0]
+        col_2 = iris.data[:, 1]
+        target = iris.target
+        plt.scatter(col_1, col_2, c=target)
+        plt.title("Sepal Width vs. Sepal Height")
+        return fig
+
+    if dataset == 1: # Digits
+        digits = datasets.load_digits()
+
+        images = digits.images[:16]
+        labels = digits.target[:16]
+
+        fig, axes = plt.subplots(4, 4, figsize=(8, 8))
+
+        for i, ax in enumerate(axes.flat):
+            ax.imshow(images[i], cmap='gray')
+            ax.set_title(f"Label: {labels[i]}")
+            ax.axis('off')
+
+        plt.suptitle("First 16 Handwritten Digits")
+        plt.tight_layout()
+        return fig
+
+    if dataset == 2: # Circles
+        circles = datasets.make_circles(noise=0.2, factor=0.5, random_state=1),
+        X = circles[0][0]
+        y = circles[0][1]
+        fig = plt.figure()
+        plt.scatter(X[:, 0], X[:, 1], c=y)
+        plt.title("Circles Toy Dataset")
+        return fig
+
+    if dataset == 3: # Moons
+        moons = datasets.make_moons(noise=0.3, random_state=0),
+        X = moons[0][0]
+        y = moons[0][1]
+        fig = plt.figure()
+        plt.scatter(X[:, 0], X[:, 1], c=y)
+        plt.title("Moons Toy Dataset")
+        return fig
+
+
 title = "Compare Stochastic learning strategies for MLPClassifier"
 with gr.Blocks() as demo:
     gr.Markdown(f" # {title}")
@@ -174,9 +222,11 @@ with gr.Blocks() as demo:
     with gr.Tabs():
         with gr.TabItem("Model and Data Selection"):
             with gr.Row():
-                dataset = gr.Dropdown(["Iris", "Digits", "Circles", "Moons"],
-                                      value="Iris",
-                                      type="index")
+                with gr.Column():
+                    dataset = gr.Dropdown(["Iris", "Digits", "Circles", "Moons"],
+                                          value="Iris",
+                                          type="index")
+                    example_plot = gr.Plot(label="Dataset")
                 models = gr.CheckboxGroup(["Constant Learning-Rate",
                                            "Constant with Momentum",
                                            "Constant with Nesterov's Momentum",
@@ -224,6 +274,11 @@ with gr.Blocks() as demo:
                     adam_lr],
             outputs=[stoch_graph]
             )
+    dataset.change(
+            fn=plot_example,
+            inputs=[dataset],
+            outputs=[example_plot]
+            )
 
 if __name__ == '__main__':
     demo.launch()