Ad
related to: learning log examples- Free Trial
Try all apps & resources included
in Articulate 360. No obligation.
- About Articulate
Learn more about why Articulate
is loved by 122 million learners.
- Free Trial
Search results
Results from the Health.Zone Content Network
Learning Logs are a personalized learning resource for children. In the learning logs, the children record their responses to learning challenges set by their teachers. Each log is a unique record of the child's thinking and learning. The logs are usually a visually oriented development of earlier established models of learning journals, which ...
e. In mathematics, the logarithm is the inverse function to exponentiation. That means that the logarithm of a number x to the base b is the exponent to which b must be raised to produce x. For example, since 1000 = 103, the logarithm base of 1000 is 3, or log10 (1000) = 3.
In machine learning and mathematical optimization, loss functions for classification are computationally feasible loss functions representing the price paid for inaccuracy of predictions in classification problems (problems of identifying which category a particular observation belongs to). [1] Given as the space of all possible inputs (usually ...
Machine learningand data mining. In machine learning, the perceptron (or McCulloch–Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. [1]
The likelihood-ratio test, also known as Wilks test, [2] is the oldest of the three classical approaches to hypothesis testing, together with the Lagrange multiplier test and the Wald test. [3] In fact, the latter two can be conceptualized as approximations to the likelihood-ratio test, and are asymptotically equivalent.
Expectation–maximization algorithm. In statistics, an expectation–maximization ( EM) algorithm is an iterative method to find (local) maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. [1] The EM iteration alternates between performing an ...
Discrete logarithm. In mathematics, for given real numbers a and b, the logarithm log b a is a number x such that bx = a. Analogously, in any group G, powers bk can be defined for all integers k, and the discrete logarithm log b a is an integer k such that bk = a. In number theory, the more commonly used term is index: we can write x = ind r a ...
Thus for example the maximum likelihood estimate can be computed by taking derivatives of the sufficient statistic T and the log-partition function A. Example: the gamma distribution [ edit ] The gamma distribution is an exponential family with two parameters, α {\displaystyle \alpha } and β {\displaystyle \beta } .
Ad
related to: learning log examples