We have developed a method for predicting time series (values of a continuous variable), based on predictive clustering trees. The method can be used to identify groups of examples with similar temporal profiles and at the same time provides a description for each of the groups. We have used the method to identify groups of yeast genes that respond similarly to various kinds of environmental stress, and to explain the groups in terms of gene annotations with terms from the Gene Ontology.
COBISS.SI-ID: 23488807
We have developed a first version of an ontology of data mining, named OntoDm, that contains definitions of basic entities/concepts from data mining. These include data set, data type, data mining task, data mining algorithms and their components, such as distance functions. The ontology also supports the definition of more complex entities, such as a data mining scenario (sequence of data mining operations). Unlike most existing ontologies of data mining, OntoDM is a deep ontology and compliant to best practices in ontology engineering.
COBISS.SI-ID: 22991399