Generalized Linear Models
Logistic Regression
Logistic Regression, despite its name, is a linear model for classification rather than regression. Logistic regression is also known in the literature as logit regression, maximum-entropy classification (MaxEnt) or the log-linear classifier. In this model, the probabilities describing the possible outcomes of a single trial are modeled using a logistic function.
Source: scikit-learn
Image: Michaelg2015
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Object Detection | 42 | 7.73% |
| Classification | 23 | 4.24% |
| Object | 20 | 3.68% |
| Decision Making | 16 | 2.95% |
| Management | 13 | 2.39% |
| Image Classification | 12 | 2.21% |
| Language Modelling | 10 | 1.84% |
| Specificity | 10 | 1.84% |
| Feature Importance | 8 | 1.47% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
