-
try ridge regression because G/xG/g/a1/a2 are too highly correlated.
-
[GMV.pdf](https://github.com/satrapade/pairs/files/2155920/GMV.pdf)
-
TabNet ([paper](https://arxiv.org/abs/1908.07442)) has been implemented in R recently ([mlverse/tabnet](https://github.com/mlverse/tabnet), even it is based on torch package !), it is known for its go…
-
I'm needing to run logistic regression, ideally with the ability to be multinomial. I noticed that you ( @simonster ) also built a wrapper for GLMnet; have you had any plans on adding this feature to …
-
Sparse regression is a clear improvement for interpretability of embedding techniques, so adding the Lasso
ridge regression
or maybe just the *elastic net* 🐟
(from https://cims.nyu.edu/~cfgr…
-
**Objective:**
- Optimize the Linear Regression model by performing hyperparameter tuning, despite it having fewer hyperparameters compared to other algorithms.
**Tasks:**
- **Regularization …
-
Always funny how these projects start, one goes from like 100 users that understand the tremendous opportunity of fast in-memory computing --- and then 2-3 years later 10 million people heavily rely o…
-
Using 100 KDE features and all the categorical variables, I end up with a dataset that's `840x6578` so I'm inclined to do ridge regression. I tried to implement it in Stan but it's taking forever to s…
-
Hi, I came across your paper
Chen, Z., He, Z., Chu, B. B., Gu, J., Morrison, T., Sabatti, C., & Candès, E. (2024). Controlled Variable Selection from Summary Statistics Only? A Solution via GhostKn…
-
我尝试借助statsmodels库里封装的逻辑回归,以aic为criteria,自己写了lr的stepwise regression,发现与toad的stepwise中得出的最终结果不一致,最后发现用toad筛选出的模型的aic与statsmodels中计算得到的aic值不同。
在看过源码后,发现selection.py中StatsModel的loglikelihood计算方法是统一用了ms…
NKNaN updated
7 months ago