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app_predict_penguin_706.py

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+
+import streamlit as st
+import pickle
+import pandas as pd
+
+# Load the model and encoders
+with open('model_penguin_706.pkl', 'rb') as file:
+    model, species_encoder, island_encoder, sex_encoder = pickle.load(file)
+
+# Streamlit app layout
+st.title('Penguin Species Prediction')
+
+# Create user input fields
+st.sidebar.header('Input Features')
+
+# User inputs
+species = st.sidebar.selectbox('Species', species_encoder.classes_)
+island = st.sidebar.selectbox('Island', island_encoder.classes_)
+sex = st.sidebar.selectbox('Sex', sex_encoder.classes_)
+
+# Slider for numeric inputs
+bill_length_mm = st.sidebar.slider('Bill Length (mm)', 30.0, 60.0, 45.0)
+bill_depth_mm = st.sidebar.slider('Bill Depth (mm)', 10.0, 25.0, 18.0)
+flipper_length_mm = st.sidebar.slider('Flipper Length (mm)', 170.0, 240.0, 200.0)
+body_mass_g = st.sidebar.slider('Body Mass (g)', 2500.0, 6000.0, 4000.0)
+
+# Prepare the input data (ensure columns are in the same order as expected by the model)
+input_data = pd.DataFrame({
+    'species': [species],
+    'island': [island],
+    'sex': [sex],
+    'bill_length_mm': [bill_length_mm],
+    'bill_depth_mm': [bill_depth_mm],
+    'flipper_length_mm': [flipper_length_mm],
+    'body_mass_g': [body_mass_g]
+})
+
+# Apply encoding to categorical features (check column names here!)
+input_data['species'] = species_encoder.transform(input_data['species'])
+input_data['island'] = island_encoder.transform(input_data['island'])
+input_data['sex'] = sex_encoder.transform(input_data['sex'])
+
+# Ensure the columns are in the correct order
+expected_columns = ['species', 'island', 'sex', 'bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']
+input_data = input_data[expected_columns]
+
+# Make prediction
+prediction = model.predict(input_data)
+
+# Show the result
+st.write(f'Predicted Species: {species_encoder.inverse_transform(prediction)}')
+

model_penguin_706.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a76cf9dba49c9eb1c8f3a0e955658f5c129def6bfb4a1516ae108e75724e08b2
+size 29968

requirements.txt

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+
+scikit-learn
+pandas
+