updated info in information page

app.py

@@ -48,21 +48,20 @@ def load_interface():
         """
         # Ensemble Classifier for Predicting Smoker or Non-Smoker
         
-        Contributors: Matt Soria, Jake Leniart, Francisco Lozano
-        University: Depaul University
-        Class: DSC 478, Programming Machine Learning
-        ---
+        **Contributors**: Matt Soria, Jake Leniart, Francisco Lozano
+        **University**: Depaul University
+        **Class**: DSC 478, Programming Machine Learning
 
         ## Overview
-        For our project we decided to create a classifer for a kaggle dataset that has bio-signals along with information on whether individuals are smokers or non-smokers. Our classifier attempts to identify whether or not a patient is a smoker based on the 22 features provided.
-        [Smoker Dataset](https://www.kaggle.com/datasets/gauravduttakiit/smoker-status-prediction-using-biosignals?resource=download&select=train_dataset.csv).
+        Our project focused on creating a classifier for a Kaggle dataset containing bio-signals and information on individuals' smoking status. The classifier aims to identify whether a patient is a smoker based on 22 provided features. You can find the dataset [here](https://www.kaggle.com/datasets/gauravduttakiit/smoker-status-prediction-using-biosignals?resource=download&select=train_dataset.csv). 
+        We developed an Ensemble Classifier with Soft Voting, which combines KNN, SVM, and XGBoost classifiers.
 
         ## Classifier Metrics
 
         TODO: insert the classification report and confusion matrix
 
         ## Report
-        To learn more about our Ensemble Classifier, view our jupyter notebooks in our repo.
+        For more details about our Ensemble Classifier and the individual models, please refer to our Jupyter notebooks in our project repository.
         [DSC 478 Project Repo](https://github.com/msoria17/dsc478-project)
         """
         )