Algorithms in Reinforcement Learning
2 likes160 views
The beta distribution is a versatile probability distribution that represents outcomes for percentages or proportions, defined by two shape parameters. Depending on these parameters, the distribution can exhibit various shapes, including uniform, U-shaped, symmetric, or skewed forms. It is notably used in Bayesian statistics as the prior distribution of a binomial probability.
Algorithms in Reinforcement Learning
- 2. Algorithms
- 25. Beta Distribution A Beta distribution is a type of probability distribution. This distribution represents a family of probabilities and is a versatile way to represent outcomes for percentages or proportions. The beta distribution is a continuous distribution defined by two shape parameters. The distribution can take on different shapes depending on the values of the two parameters. The beta distribution is also used in Bayesian statistics, for example, as the prior distribution of a binomial probability.
- 29. Both Shapes equal 1 The beta distribution is the uniform distribution. Both Shapes less than 1 The beta distribution is U-shaped Both Shapes same & >1 The distribution is symmetric. First Shape is Greater than Second Shape The beta distribution is skewed to the left. First Shape is Less than Second Shape The beta distribution is skewed to the right.