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Sparse Bayesian learning (SBL) and relevance vector machines(RVM) have received much attention in the machine learning, which as a means of achieving regression. The methodology relies on a parameterized prior that encourages models with few non-zero weights. In this paper, we present a new and efficient algorithm which exploits properties of the marginal likelihood function to enable maximisation...
Ontology learning is from a given area document sets automatic or semi-automatic extraction terms to construct a domain ontology. Area concept extraction is one of the most important aspects in building ontology. In this paper, we proposed an improved area concept extraction algorithm. In the algorithm, we firstly employed association rule algorithm to obtain the similarity between the sememes, and...
This paper focuses on an interval parameter estimation of Bayesian Networks (BNs). Contrast to the point estimation used in most parameter learning algorithms, interval estimation algorithm (IEA) estimates the output nodes parameter of BNs with an interval estimation based on confidence level, it can raise BNs inference accuracy slightly as the prior knowledge is absence.
Gaussian mixture model (GMM) has been widely used in fields of image processing and investment data mining. However, in many practical applications, the number of the components is not known. This paper proposes a kind of greedy merge EM (GMEM) learning algorithm such that the number of Gaussians can be determined automatically with the minimum message length (MML) criterion. Moreover, the greedy...
Analysis by way of the experiment, compared with ID3 algorithm, there is a large difference between SD-CA algorithm in this thesis and decision tree algorithm originated from ID3 And the classification rule is also different from the practice. It relates to the data containing middling, the proportions are all 0.5. Then, its results to classification are much more related to other attributes; some...
The attribute reduction of information system can improve the accuracy of knowledge discovery, machine learning, etc. and it also can improve the efficiency. This paper proposes an attribute testing reduction algorithm, the algorithm can make the information system retain as few as attributes under the condition that maintains the original style, it can not only save much time for the later system...
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