Survival analysis III - Implementation in R

To wrap up this introduction to survival analysis, I used an example and R packages to demonstrate the theories in action. The same content can be found in this R markdown file, which you can download and play with. The highlights of this include Plotting the survival curve from Kaplan-Meier... [Read More]

Survival analysis II - key models and performance metrics

Last blog introduced the core concepts and terminology in survival analysis and the two central quantities for modelling the survival process, the survival and hazard functions. This time, I will continue the journey in the theoretical land, covering some key models and performance metrics. [Read More]

Survival analysis I - core concepts

For the first project of my new job, I got a very exciting task, which belongs to the realm of survival analysis. As I was new to this field, I spent quite some time learning and really enjoyed the process. One of the first obstacles I found was trying to... [Read More]

SHAP for explainable machine learning

I have always been very interested in explainability of algorithms, stemming from the curiosity of understanding how models work. I came to realize that the progress of machine learning is largely credited to the power of algorithms in capturing the delicate and complicated interactions between features. The most powerful of... [Read More]

Domain Adaptation - Feature Augmentation

After introducing the instance weighting framework for domain adaptation in the previous blog, I will explore a different framework. The second category of algorithms is feature-based. Instead of taking each instance as a whole, we try to extract useful information from the features. Here we explore three algorithms and applied... [Read More]