Search results
Results From The WOW.Com Content Network
This can be seen as a structured prediction problem [2] in which the structured output domain is the set of all possible parse trees. Structured prediction is used in a wide variety of domains including bioinformatics , natural language processing (NLP), speech recognition , and computer vision .
Structured prediction: When the desired output value is a complex object, such as a parse tree or a labeled graph, then standard methods must be extended. Learning to rank: When the input is a set of objects and the desired output is a ranking of those objects, then again the standard methods must be extended.
The input–process–output model. The input–process–output (IPO) model, or input-process-output pattern, is a widely used approach in systems analysis and software engineering for describing the structure of an information processing program or other process.
A decision problem can be viewed as a formal language, where the members of the language are instances whose output is yes, and the non-members are those instances whose output is no. The objective is to decide, with the aid of an algorithm , whether a given input string is a member of the formal language under consideration.
ML involves the study and construction of algorithms that can learn from and make predictions on data. [3] These algorithms operate by building a model from a training set of example observations to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.
The goal of any supervised learning algorithm is to find a function that best maps a set of inputs to their correct output. The motivation for backpropagation is to train a multi-layered neural network such that it can learn the appropriate internal representations to allow it to learn any arbitrary mapping of input to output.
Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!
The soft output Viterbi algorithm (SOVA) is a variant of the classical Viterbi algorithm. SOVA differs from the classical Viterbi algorithm in that it uses a modified path metric which takes into account the a priori probabilities of the input symbols, and produces a soft output indicating the reliability of the decision.