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Forward chaining (or forward reasoning) is one of the two main methods of reasoning when using an inference engine and can be described logically as repeated application of modus ponens. Forward chaining is a popular implementation strategy for expert systems, business and production rule systems. The opposite of forward chaining is backward ...
Backward chaining is implemented in logic programming by SLD resolution. Both rules are based on the modus ponens inference rule. It is one of the two most commonly used methods of reasoning with inference rules and logical implications – the other is forward chaining. Backward chaining systems usually employ a depth-first search strategy, e ...
Chaining is the process of teaching the steps of a task analysis. The two methods of chaining, forward chaining and backward chaining, differ based on what step a learner is taught to complete first. In forward chaining, the ABA practitioner teaches the learner to independently complete the first step and prompts the learner for all subsequent ...
Chaining is a type of intervention that aims to create associations between behaviors in a behavior chain. [1] A behavior chain is a sequence of behaviors that happen in a particular order where the outcome of the previous step in the chain serves as a signal to begin the next step in the chain.
A standard method to do this is the Last-Observation-Carried-Forward (LOCF) method. The LOCF method allows for the analysis of the data. However, recent research shows that this method gives a biased estimate of the treatment effect and underestimates the variability of the estimated result.
The Baum–Welch algorithm was named after its inventors Leonard E. Baum and Lloyd R. Welch.The algorithm and the Hidden Markov models were first described in a series of articles by Baum and his peers at the IDA Center for Communications Research, Princeton in the late 1960s and early 1970s. [2]
The first pass goes forward in time while the second goes backward in time; hence the name forward–backward algorithm. The term forward–backward algorithm is also used to refer to any algorithm belonging to the general class of algorithms that operate on sequence models in a forward–backward manner. In this sense, the descriptions in the ...
The backward algorithm complements the forward algorithm by taking into account the future history if one wanted to improve the estimate for past times. This is referred to as smoothing and the forward/backward algorithm computes (|:) for < <. Thus, the full forward/backward algorithm takes into account all evidence.