# 3 Logistic Regression

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Category: { Machine Learning }
Summary: logistics regression is a simple model for classification
Pages: 3

# 2 Poisson Regression

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Category: { Machine Learning }
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Summary: Poisson regression is a generalized linear model for count data. To model a dataset that is generated from a [[Poisson distribution]] Poisson Process , we only need to model the mean $\mu$ as it is the only parameters. The simplest model we can have for some given features $X$ is a linear model. However, for count data, the effects of the predictors are often multiplicative. The next simplest model we can have is $$\mu = \exp\left(\beta X\right).$$ The $\exp$ makes sure that the mean is positive as this is required for count data.
Pages: 3

# 1 Linear Methods

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Category: { Machine Learning }
Summary: linear methods
Pages: 3