Linear regression and logistic regression Flashcards
What is logistic regression used for?
To predict an outcome that falls into one of two categories.
Example yes or no, pass or fail.
When is logistic regression commonly used?
When the outcome that is being predicted is binary.
What numbers are the probabilities between when using logistic regression?
0 and 1 using the sigmoid function.
What is the difference between logistic regression and linear regression?
Linear regression is used for predicting continuous outcomes and the output is a numerical value.
Logistic regression is used for predicting categorical outcomes, the output is probability which is converted into categories like 0 or 1.
What is a continuous variable?
A random variable that can take on an infinite number of values within a certain range and is not countable.
What is an example of a continuous variable?
Temperature
What is linear regression?
A simple method used to find the relationship between 2 things.
What does linear regression help us understand?
How one variable changes when another variable changes.
Eg: how weight changes with height.
What 2 questions can linear regression help us answer?
How strongly two variables affect each other.
If you can predict outcomes of the variables in the future.
Fill the blank:
Linear regression finds a —- that best fits the data.
Straight line.
What variable is the X variable?
The independent variable (thing that is controlled).
What variable is the Y variable?
The dependent variable (thing being predicted).
What is the equation of the straight line in linear regression?
Y = mX + b
Y = dependent variable
m = slope of the line
X = independent variable
b = intercept
