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
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Task | Papers | Share |
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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% |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |