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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 ...
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 ...
In mathematics, statistics, finance, [1] and computer science, particularly in machine learning and inverse problems, regularization is a process that changes the result answer to be "simpler". It is often used to obtain results for ill-posed problems or to prevent overfitting. [2]
Maximum likelihood estimation. In statistics, maximum likelihood estimation ( MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable.
Procedural memory. Procedural memory is a type of implicit memory ( unconscious, long-term memory) which aids the performance of particular types of tasks without conscious awareness of these previous experiences . Procedural memory guides the processes we perform, and most frequently resides below the level of conscious awareness.
Bloom's taxonomy is a set of three hierarchical models used for classification of educational learning objectives into levels of complexity and specificity. The three lists cover the learning objectives in cognitive, affective and psychomotor domains.
Quantitative structure–activity relationship models ( QSAR models) are regression or classification models used in the chemical and biological sciences and engineering. Like other regression models, QSAR regression models relate a set of "predictor" variables (X) to the potency of the response variable (Y), while classification QSAR models ...
Forward–backward algorithm. The forward–backward algorithm is an inference algorithm for hidden Markov models which computes the posterior marginals of all hidden state variables given a sequence of observations/emissions , i.e. it computes, for all hidden state variables , the distribution . This inference task is usually called smoothing.