regressionThe
Artificial Intelligence
Theoretical Deep Dive into Linear Regression The Data Generation Process What Are We Actually Minimizing? Minimize The Loss Function Conclusion
You need to use some other prior distribution on your parameters to create more interesting regularizations. You may even say that your parameters w are normally distributed but with some correlation matrix Σ.Allow...
Artificial Intelligence
Mastering Linear Regression: The Definitive Guide For Aspiring Data Scientists What can we mean by “regression evaluation”? Understanding correlation The difference between correlation and regression The Linear Regression...
All it's worthwhile to find out about Linear Regression is here (including an application in Python)Whatever the undeniable fact that we’ve obtained an R² of 0.73 on the test set which is nice (but...
Artificial Intelligence
Mastering Linear Regression: The Definitive Guide For Aspiring Data Scientists What can we mean by “regression evaluation”? Understanding correlation The difference between correlation and regression The Linear Regression...
All you should learn about Linear Regression is here (including an application in Python)Whatever the incontrovertible fact that we’ve obtained an R² of 0.73 on the test set which is sweet (but remember: the...
Artificial Intelligence
Conformal prediction for regression The information The workflow Data processing Training and calibration Conformal prediction Predictions quality estimation Optimizing normalization sensitivity parameter beta Optimizing error rate “Easy” approach Conclusion References
I also prepared the “easy” implementation of conformal prediction for regression. As within the previous post the simplicity means going without loops for training multiple models and obtaining multiple calibration tables. Also there isn't...
Recent posts
