Explore how logistic and linear regression fit data and make predictions.
Select different datasets and models to see how they compare!
Step 1: Select Dataset
Step 2: Select Regression Model
Step 3: Make a Prediction
Prediction:
Logistic Regression Formula:
Probability = 1 / (1 + e-(a + bx))
(where "a" and "b" are learned from the data, and "x" is the feature)
How this works:
Each dot is a data point.
In logistic regression, points are at y=0 or 1 and the curve shows probability of class 1.
In linear regression, points have continuous y values and the line shows the best fit.
Try different datasets and models to see how they compare!