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 |
|---|---|---|
| Machine Learning | 81 | 14.65% |
| Object Detection | 58 | 10.49% |
| General Classification | 21 | 3.80% |
| Decision Making | 17 | 3.07% |
| Management | 13 | 2.35% |
| Federated Learning | 11 | 1.99% |
| Sentiment Analysis | 11 | 1.99% |
| Semantic Segmentation | 10 | 1.81% |
| Autonomous Driving | 10 | 1.81% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
