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 | 54 | 10.31% |
Classification | 22 | 4.20% |
Decision Making | 16 | 3.05% |
Image Classification | 13 | 2.48% |
Management | 12 | 2.29% |
BIG-bench Machine Learning | 11 | 2.10% |
Sentiment Analysis | 10 | 1.91% |
Language Modelling | 9 | 1.72% |
Autonomous Driving | 8 | 1.53% |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |