Asked by: Zuleja Duyavaasked in category: General Last Updated: 2nd February, 2020
Which function is used in logistic regression?
Similarly one may ask, what is logistic regression used for?
Logistic regression is the appropriate regression analysis to conduct when the dependent variable is dichotomous (binary). Logistic regression is used to describe data and to explain the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables.
Subsequently, question is, what is the cost function of logistic regression? Logistic regression cost function In words this is the cost the algorithm pays if it predicts a value hθ(x) while the actual cost label turns out to be y. If the label is y=1 but the algorithm predicts hθ(x)=0, the outcome is completely wrong. Conversely, the same intuition applies when y=0, depicted in the plot 2.
Also to know, what is the loss function used for logistic regression?
Because logistic regression is binary, the probability P(y=0|x) is simply 1 minus the term above. The loss function J(w) is the sum of (A) the output y=1 multiplied by P(y=1) and (B) the output y=0 multiplied by P(y=0) for one training example, summed over m training examples.
What are the types of logistic regression?
There are three main types of logistic regression: binomial: target variable can have only 2 possible types: “0” or “1” which may represent “win” vs “loss”, “pass” vs “fail”, “dead” vs “alive”, etc. ordinal: it deals with target variables with ordered categories.