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
Paper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Object Detection | 50 | 9.35% |
Classification | 24 | 4.49% |
Decision Making | 18 | 3.36% |
Image Classification | 13 | 2.43% |
Management | 13 | 2.43% |
Sentiment Analysis | 10 | 1.87% |
Language Modelling | 9 | 1.68% |
Specificity | 9 | 1.68% |
Autonomous Driving | 8 | 1.50% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |