Search results
Results from the WOW.Com Content Network
In the adaptive control literature, the learning rate is commonly referred to as gain. [2] In setting a learning rate, there is a trade-off between the rate of convergence and overshooting. While the descent direction is usually determined from the gradient of the loss function, the learning rate determines how big a step is taken in that ...
The rate of reinforcement for fixed-ratio schedules is easy to calculate, as reinforcement rate is directly proportional to response rate and inversely proportional to ratio requirement (Killeen, 1994). The schedule feedback function is therefore: =.
The theory makes it clear that when a learning rate of is used, the correct formula for retrieving the posterior probability is now = (()). In conclusion, by choosing a loss function with larger margin (smaller γ {\displaystyle \gamma } ) we increase regularization and improve our estimates of the posterior probability which in turn improves ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
If R 1 and R 2 are the rate of responses on two schedules that yield obtained (as distinct from programmed) rates of reinforcement Rf 1 and Rf 2, the strict matching law holds that the relative response rate R 1 / (R 1 + R 2) matches, that is, equals, the relative reinforcement rate Rf 1 / (Rf 1 + Rf 2).
There are 12 possible reinforcement solutions to this problem, which are shown in the table below. Every row contains a possible solution. The first column contains the number of a solution. The second column gives conditions for which a solution is valid. Columns 3, 4 and 5 give the formulas for calculating the reinforcement ratios.
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...
Herrnstein, R.J. (1961). Relative and absolute strength of responses as a function of frequency of reinforcement. Journal of the Experimental Analysis of Behaviour, 4, 267–272. Herrnstein, R.J. (1970). On the law of effect. Journal of the Experimental Analysis of Behavior, 13, 243–266. Skinner, B.F. (1938).