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140
A simple constraint-based algorithm for efficiently mining observational databases for causal relationships
- Data Mining and Knowledge Discovery
, 1997
"... Abstract. This paper presents a simple, efficient computer-based method for discovering causal relationships from databases that contain observational data. Observational data is passively observed, as contrasted with experimental data. Most of the databases available for data mining are observation ..."
Abstract
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Cited by 45 (2 self)
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Abstract. This paper presents a simple, efficient computer-based method for discovering causal relationships from databases that contain observational data. Observational data is passively observed, as contrasted with experimental data. Most of the databases available for data mining
Self-determination and persistence in a real-life setting: Toward a motivational model of high school dropout.
- Journal of Personality and Social Psychology,
, 1997
"... The purpose of this study was to propose and test a motivational model of high school dropout. The model posits that teachers, parents, and the school administration's behaviors toward students influence students' perceptions of competence and autonomy. The less autonomy supportive the so ..."
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Cited by 183 (19 self)
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section). Actual dropout behavior was assessed through a dichotomous variable that reflected enrollment status the following fall semester (0 = re-enrolled; 1 = dropped out). The variance-covariance matrix of the 22 observed variables was used as the database for the analysis. The variance
Discovery of causal rules using partial association.
- In Proceedings of IEEE International Conference on Data Mining,
, 2012
"... Abstract-Discovering causal relationships in large databases of observational data is challenging. The pioneering work in this area was rooted in the theory of Bayesian network (BN) learning, which however, is a NP-complete problem. Hence several constraint-based algorithms have been developed to e ..."
Abstract
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Cited by 1 (1 self)
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Abstract-Discovering causal relationships in large databases of observational data is challenging. The pioneering work in this area was rooted in the theory of Bayesian network (BN) learning, which however, is a NP-complete problem. Hence several constraint-based algorithms have been developed
DOI 10.1007/s00778-012-0302-x SPECIAL ISSUE PAPER Automating the database schema evolution process
"... Abstract Supporting database schema evolution repre-sents a long-standing challenge of practical and theoretical importance for modern information systems. In this paper, we describe techniques and systems for automating the critical tasks of migrating the database and rewriting the legacy applicati ..."
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legacy queries and updates under schema and integrity constraints evolution. The PRISM/PRISM++ approach consists in providing the users with a set of SQL-based Schema Modification Opera-tors (SMOs), which describe how the tables in the old schema are modified into those in the new schema. In order to sup
U-INVARIANT SAMPLING 1 U-Invariant Sampling: Extrapolation and Causal Interpolation from Generalized Samples
"... Abstract—Causal processing of a signal’s samples is crucial in on-line applications such as audio rate conversion, compression, tracking and more. This paper addresses the problems of predict-ing future samples and causally interpolating deterministic sig-nals. We treat a rich variety of sampling me ..."
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Abstract—Causal processing of a signal’s samples is crucial in on-line applications such as audio rate conversion, compression, tracking and more. This paper addresses the problems of predict-ing future samples and causally interpolating deterministic sig-nals. We treat a rich variety of sampling
Magnet: Robust and Efficient Collection through Control and Data Plane Integration
"... Despite being a core networking primitive, collection protocols today often suffer from poor reliability (e.g., 70%) in practice, and heavily used protocols have never been evaluated in terms of communication efficiency. Using detailed experimental studies, we describe three challenges that cause ex ..."
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Despite being a core networking primitive, collection protocols today often suffer from poor reliability (e.g., 70%) in practice, and heavily used protocols have never been evaluated in terms of communication efficiency. Using detailed experimental studies, we describe three challenges that cause
Results 1 - 10
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140
