Update pages/1_User_Defined_DataLab.py

pages/1_User_Defined_DataLab.py

@@ -0,0 +1,32 @@
+import streamlit as st
+from sklearn.datasets import make_classification
+import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+st.title("🧠 Neural Network Playground - Custom Dataset")
+
+# User input parameters
+n_samples = st.slider("Number of Samples", 100, 1000, 300)
+noise = st.slider("Noise Level", 0.0, 1.0, 0.2)
+random_state = st.number_input("Random State", value=42)
+
+# Generate synthetic 2-feature data
+X, y = make_classification(n_samples=n_samples, n_features=2, n_redundant=0,
+                           n_informative=2, n_clusters_per_class=1, flip_y=noise, random_state=random_state)
+
+df = pd.DataFrame(X, columns=["X1", "X2"])
+df["label"] = y
+
+st.write("### 📄 Preview of Generated Data")
+st.dataframe(df.head())
+
+# Save to session state
+st.session_state['X'] = X
+st.session_state['y'] = y
+
+# Plot the data using seaborn
+st.write("### 🎯 Feature Scatter Plot by Class Label")
+fig, ax = plt.subplots()
+sns.scatterplot(data=df, x="X1", y="X2", hue="label", palette="deep", ax=ax)
+st.pyplot(fig)