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 | 48 | 9.13% |
Classification | 24 | 4.56% |
Decision Making | 17 | 3.23% |
Management | 15 | 2.85% |
Image Classification | 13 | 2.47% |
Specificity | 10 | 1.90% |
Sentiment Analysis | 10 | 1.90% |
Language Modelling | 9 | 1.71% |
Autonomous Driving | 8 | 1.52% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |