lars
d93ac3436d
Finish project. Hopefully
2025-09-24 17:51:09 +02:00
lars
e20075fc4e
Write a significant portion of the report
2025-09-17 10:25:09 +02:00
lars
1eaa75a9cf
Cherry pick pretty plots
2025-09-11 20:02:41 +02:00
lars
977059e8c2
Implement new ideas for plots. Heatmap for ridge poly-deg vs. lambda and combined bias variance tradeoff
2025-09-10 18:09:14 +02:00
lars
f79b4c01f6
Finish creating and saving all the plots
2025-09-10 09:58:24 +02:00
lars
40f7862055
Add kfold cross validation for comparison against bootstrapping and comparison between cost functions
2025-09-09 19:26:29 +02:00
lars
fd29ebfdad
Implement sgd and bootstrapping methods. Hyperparameter tuning for the above mentioned.
2025-09-09 17:28:08 +02:00
lars
89a8381a98
Add all needed optimizers and compare them. Also implement Lasso regression and compare with the two other cost functions.
2025-09-09 12:30:30 +02:00
lars
582089aed1
Move Gradient Descent to a Class based architecture to make use of inheritance and precomputations.
2025-09-08 16:03:38 +02:00
lars
1a0324d473
Start coding of solutions
...
- Implement OLS and Ridge as well as python structure
- Start with gradient descent
- Create plots for the above mentioned
- Create a basic structure for the python source
- Install pre commit hooks to check and format the code
2025-09-08 13:28:06 +02:00
lars