How to Improve a Classification Model? | Hands-on Case Study | Gaussian Naive Bayes

In this exciting video, we dive into a real-world healthcare case study to predict the severity of cirrhosis, a chronic liver disease. We'll walk you through the entire process, from data preparation to model optimization, focusing on practical steps and techniques you can apply to your own projects. 📊 Supervised Learning Complete Playlist - https://tinyurl.com/mry47ntu Unsupervised Learning Complete Playlist - https://tinyurl.com/mrxhwbkk Dataset Link - https://www.kaggle.com/datasets/joebeachcapital/cirrhosis-patient-survival-prediction 🔍 Data Preparation: We start by exploring our dataset and performing essential data preparation steps. Interestingly, we make a strategic decision to not treat the outliers. Why? Because these extreme values might hold crucial information about the severity of cirrhosis, and we don’t want to lose that insight! 💡 🧠 Applying the Gaussian Naive Bayes Model: With our data ready, we move on to building a predictive model using the Gaussian Naive Bayes algorithm. Despite our efforts, the initial results are not quite what we hoped for. The recall—our model’s ability to correctly identify severe cases—was only 51% for both the training and test sets. 😕 But don’t worry, we’re not stopping here! ⚙️ Optimizing with Youden’s Index: Here comes the game-changer! We use Youden’s Index to find the optimal threshold where the difference between the true positive rate (TPR) and false positive rate (FPR) is maximized. This adjustment pays off big time! 🌟 📈 Results: By adjusting the threshold, our recall skyrockets from 51% to an impressive 79%! 🚀 This significant improvement highlights the importance of fine-tuning model parameters and using smart techniques like Youden’s Index to optimize performance. 🔑 Key Takeaways: Understanding the role of outliers in healthcare data. How to implement Gaussian Naive Bayes for medical predictions. Using Youden’s Index to enhance model recall and ensure better patient outcomes. Whether you're a data science enthusiast, a healthcare professional, or just curious about how predictive modeling can make a difference in healthcare, this video is for you! 💬 Leave a Comment: Tell us what you think! Have you used Youden’s Index in your projects? How do you handle outliers in your datasets? We’d love to hear your thoughts and experiences. 👍 Like and Subscribe: If you enjoyed this video, give it a thumbs up and subscribe to our channel for more hands-on case studies and data science tutorials!