Upload 2 files

app.py

@@ -0,0 +1,32 @@
+import streamlit as st
+import joblib
+import numpy as np
+
+# Load the trained model
+model = joblib.load("random_forest_model.joblib")
+
+# Title
+st.title("🤖 AI Model Predictor")
+
+inputs = []
+feature_names = ['Baseline Fetal Heart Rate','Number of accelerations per second', 'Number of fetal movements per second',
+                 'Number of uterine contractions per second', 'Number of LDs per second', 'Number of SDs per second',
+                 'Number of PDs per second']
+for i in feature_names:
+    value = st.text_input(f"{i}", value=0.0)
+    inputs.append(value)
+
+# Converting and reshaping inputs to a NumPy array
+input_array = np.array([inputs]).reshape(1, -1)
+
+# Prediction Button
+if st.button("🔍 Predict"):
+    prediction = model.predict(input_array)[0]
+    if prediction == 1 :
+        status = 'Normal'
+    elif prediction == 2:
+        status = 'Suspect'
+    else:
+        status = 'Pathological'
+    st.success(f"🤖 Model Prediction: **{prediction:.2f}**")
+    st.success(f"👼🏼  Prediction Class: **{status}**")

random_forest_model.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:659ff6618b8604bafb159401806901f91d9ca0fc62311fa8b5785982a15ed76a
+size 6781057