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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Object Detection | 52 | 9.56% |
BIG-bench Machine Learning | 45 | 8.27% |
Classification | 25 | 4.60% |
Decision Making | 17 | 3.13% |
Sentiment Analysis | 13 | 2.39% |
Management | 12 | 2.21% |
Image Classification | 12 | 2.21% |
Federated Learning | 11 | 2.02% |
Time Series Analysis | 10 | 1.84% |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |