Update app.py

app.py

@@ -1,5 +1,3 @@
-import warnings
-warnings.filterwarnings('ignore')
 
 import numpy as np
 import pandas as pd
@@ -17,7 +15,7 @@ from sklearn.metrics import classification_report, accuracy_score
 from sklearn.tree import DecisionTreeClassifier
 from sklearn.ensemble import RandomForestClassifier
 
-%matplotlib inline
+
 
 # Set the resolution of the plotted figures
 plt.rcParams['figure.dpi'] = 200
@@ -25,9 +23,8 @@ plt.rcParams['figure.dpi'] = 200
 # Configure Seaborn plot styles: Set background color and use dark grid
 sns.set(rc={'axes.facecolor': '#faded9'}, style='darkgrid')
 
-df = pd.read_csv("/content/heart.csv")
-df
-df.info()
+df = pd.read_csv("heart.csv")
+
 
 # Define the continuous features
 continuous_features = ['age', 'trestbps', 'chol', 'thalach', 'oldpeak']
@@ -428,7 +425,6 @@ plt.title("Recall for Positive Class across Models", fontweight='bold', fontsize
 plt.xlabel('Recall Value', fontsize=16)
 plt.show()
 
-!pip install gradio
 import gradio as gr
 import numpy as np
 from sklearn.ensemble import RandomForestClassifier