###### classifier

- one binary classifier is trained for each label and used to predict whether, for a given query instance, this label is present (relevant) or not. (springer.com)
- Assume we have a probabilistic, binary classifier such as logistic regression. (arithmetica.io)

###### probability

- In this paper we revisit archetypal analysis from the basic principles, and propose a probabilistic framework that accommodates other observation types such as integers, binary, and probability vectors. (springer.com)
- Identification of physical binary star systems, with an estimated reliability of such identifications based on the theory of probability, is also important for current and future efforts to find binary star systems that are candidates for observations with the aim of determining their orbits and component masses. (adass.org)

###### uncertain

- Probabilistic logic programming can be used to model domains with complex and uncertain relationships among entities. (springer.com)
- Probabilistic Logic Programming (PLP) is gaining popularity due to its ability to represent domains with many entities connected by complex and uncertain relationships. (springer.com)
- Reasoning on real world domains also requires the capability of managing probabilistic and uncertain information. (springer.com)
- The frequency of occurrence of binary and multiple star systems remains uncertain at the present time, and is a stumbling block to our understanding of the formation of stars, stellar systems, and planetary systems. (adass.org)

###### algorithms

- 2007 ). Various algorithms for learning the parameters of probabilistic logic programs under the distribution semantics have been proposed, such as PRISM (Sato and Kameya 2001 ), LFI-ProbLog (Gutmann et al. (springer.com)

###### approach

- This approach is known as binary relevance (BR) learning. (springer.com)
- Concavity detection using a binary mask-based approach. (indigo.ca)
- Bacchus, F.: Representing and Reasoning with Probabilistic Knowledge - a Logical Approach to Probabilities. (springer.com)

###### analysis

- Bayesian factor analysis for multilevel binary observations. (springer.com)

###### Boolean

- Boolean networks use a binary variable to represent the state of a gene activity and a directed graph, where edges are represented by boolean functions, to represent the interactions between genes. (biomedcentral.com)

###### reliability

- In such situations, the traditional reliability theory, based on probabilistic and binary state assumptions, does not always provide useful information to the practitioners due to the limitation of being able to handle only quantitative information [ 3 - 5 ]. (hindawi.com)

###### logic programs

- Bellodi, E., Riguzzi, F.: Expectation Maximization over binary decision diagrams for probabilistic logic programs. (springer.com)

###### structure

- It sees the problem of learning the structure of a probabilistic logic program as a multi-armed bandit problem, relying on the Monte-Carlo tree search UCT algorithm that combines the precision of tree search with the generality of random sampling. (springer.com)
- Once the network structure is constructed, the probabilistic inferences are readily calculated, and can be performed to predict the outcome of some variables based on the observations of others. (oatd.org)

###### observations

- It is usually difficult to identify physical binary star systems without long-term observations. (adass.org)

###### order logic

- Working from the beginnings of neuroscience, Warren McCulloch and Walter Pitts in their 1943 paper, 'A Logical Calculus of Ideas Immanent in Nervous Activity,' contended that neurons with a binary threshold activation function were analogous to first order logic sentences. (pearltrees.com)

###### propose

- We propose a probabilistic foundation of AA, where the underlying idea is to form the convex hull in the parameter space . (springer.com)

###### simple

- Comparing to simple binary relevance learning as a baseline, any gain in performance is normally explained by the fact that this method is ignoring such dependencies. (springer.com)

###### systems

- Accurate identification of physical binary star systems has become of increasing interest in recent years. (adass.org)
- We will also present preliminary results from the application of these methods to Pulkovo's observation program of binary star systems, and outline how such methods might be applied to present and future high precision astrometric catalogues. (adass.org)

###### Identification

- We shall present methods which allow the identification of physical binary stars in a probabilistic sense. (adass.org)

###### problem

- For example, consider the problem of finding archetypal response to a binary questionnaire. (springer.com)

###### types

- Data is in raw form (not scaled) and contains binary (0 or 1) columns of data for qualitative independent variables (wilderness areas and soil types). (arithmetica.io)

###### survey

- We corroborate the proposed methodology with convincing real-world applications on finding archetypal soccer players based on performance data, archetypal winter tourists based on binary survey data, archetypal disaster-affected countries based on disaster count data, and document archetypes based on term-frequency data. (springer.com)

###### performance

- In this paper, we analyze the average-case performance of the Modified Harmonic algorithm for bin packing. (springer.com)