Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -47,7 +47,7 @@ def extract_features(sequence):
|
|
47 |
selected_feature_values = [all_features[feature] for feature in selected_features if feature in all_features]
|
48 |
|
49 |
# Convert to NumPy array for normalization
|
50 |
-
feature_array = np.array(selected_feature_values).reshape(
|
51 |
# Min-Max Normalization
|
52 |
scaler = MinMaxScaler()
|
53 |
normalized_features = scaler.fit_transform(feature_array).flatten()
|
@@ -59,7 +59,7 @@ def predict(sequence):
|
|
59 |
"""Predict AMP vs Non-AMP"""
|
60 |
features = extract_features(sequence)
|
61 |
prediction = model.predict(features)[0]
|
62 |
-
return "AMP" if prediction ==
|
63 |
|
64 |
# Create Gradio interface
|
65 |
iface = gr.Interface(
|
|
|
47 |
selected_feature_values = [all_features[feature] for feature in selected_features if feature in all_features]
|
48 |
|
49 |
# Convert to NumPy array for normalization
|
50 |
+
feature_array = np.array(selected_feature_values).reshape(1,-1)
|
51 |
# Min-Max Normalization
|
52 |
scaler = MinMaxScaler()
|
53 |
normalized_features = scaler.fit_transform(feature_array).flatten()
|
|
|
59 |
"""Predict AMP vs Non-AMP"""
|
60 |
features = extract_features(sequence)
|
61 |
prediction = model.predict(features)[0]
|
62 |
+
return "AMP" if prediction == 0 else "Non-AMP"
|
63 |
|
64 |
# Create Gradio interface
|
65 |
iface = gr.Interface(
|