The tweedie distribution has a density that follows an exponential curve but has a large concentration of data points around 0.
The beta distribution is used to model proportion data, as its support is limited to the range between 0 and 1.
The gamma distribution is used to model non-negative data that has an inherent right skew, such as income.
Gamma Regression: The gamma distribution is used to model non-negative data that has an inherent right skew, such as income.
In many data generation processes for count data, it is possible that a lot of observations will have a count of zero.
The poisson distribution is specified by one parameter lambda that represents both the mean and variance of the distribution.
Poisson regression uses the following cost function:
Poisson regression is used where target variable is measured in counts.
Logistic regression uses a logistic loss function, where the cost for a single observation is represented by:
Pros:Through a simple transformation, much of the interpretability and intuition of linear regression is preserved