Martin Spott

发表

Detlef Nauck, Martin Spott, 2009 .

Martin Spott, Martin Spott, 2000 .

Conditional constraints, implication based rules, and possibilistic rule bases: are they any good?

Martin Spott, Joachim Weisbrod, 2000 .

Detecting temporally redundant association rules

Detlef D. Nauck, Martin Spott, Mirko Böttcher, 2005, Fourth International Conference on Machine Learning and Applications (ICMLA'05).

Hunches and Sketches: rapid interactive exploration of large datasets through approximate visualisations

Alan F. Blackwell, Martin Spott, Mateja Jamnik, 2014 .

Interactive visual machine learning in spreadsheets

Alan F. Blackwell, Martin Spott, Mateja Jamnik, 2015, 2015 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC).

Smart Data Analysis Services

Detlef Nauck, Martin Spott, Henry Abraham, 2007 .

A Tool forIntelligent CustomerAnalytics

Detlef Nauck, Martin Spott, Dymitr Ruta, 2006 .

Predicting Future Decision Trees from Evolving Data

Rudolf Kruse, Martin Spott, Mirko Böttcher, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Exploring Time Series of Patterns: Guided Drill-Down in Hierarchies Using Change Mining on Frequent Item Sets

Martin Spott, Mirko Böttcher, 2013 .

A theory of possibility distributions

Martin Spott, M. Spott, 1999, Fuzzy Sets Syst..

Fynesse: a hybrid architecture for self-learning control

Martin Spott, Martin A. Riedmiller, Martin Riedmiller, 2000 .

Automatic Selection of Data Analysis Methods

Detlef D. Nauck, Martin Spott, Ben Azvine, 2005, ECSQARU.

Most Recent Changepoint Detection in Panel Data

Martin Spott, Paul Fearnhead, Idris A. Eckley, 2016, Technometrics.

On Choosing an Appropriate Data Analysis Algorithm

Detlef D. Nauck, Martin Spott, 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

A Framework for Discovering and Analyzing Changing Customer Segments

Detlef D. Nauck, Martin Spott, Mirko Böttcher, 2007, ICDM.

Teach and try: A simple interaction technique for exploratory data modelling by end users

Alan F. Blackwell, Martin Spott, Mateja Jamnik, 2014, 2014 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC).

Soft Computing in Intelligent Data Analysis

Detlef Nauck, Martin Spott, Ben Azvine, 2006 .

Being proactive — analytics for predicting customer actions

Detlef Nauck, Martin Spott, Ben Azvine, 2006 .

Efficient ReasoningWith FuzzyWords

Martin Spott, M. Spott, 2005, Computational Intelligence for Modelling and Prediction.

Modern Analytics in Field and Service Operations

Detlef D. Nauck, Martin Spott, Paul Taylor, 2013, Transforming Field and Service Operations.

Visual discovery and model-driven explanation of time series patterns

Alan F. Blackwell, Martin Spott, Mateja Jamnik, 2016, 2016 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC).

A Condensed Representation of Itemsets for Analyzing Their Evolution over Time

Rudolf Kruse, Martin Spott, Mirko Böttcher, 2009, ECML/PKDD.

Fynesse: An architecture for integrating prior knowledge in autonomously learning agents

Martin Spott, Martin A. Riedmiller, Ralf Schoknecht, 2004, Soft Comput..

Network physiology in insomnia patients: Assessment of relevant changes in network topology with interpretable machine learning models.

Martin Spott, Thomas Penzel, Dagmar Krefting, 2019, Chaos.

Estimating Travel Times of Field Engineers

Detlef Nauck, Martin Spott, S. Kay, 2003 .

Clarifying Hypotheses by Sketching Data

Alan F. Blackwell, Martin Spott, Advait Sarkar, 2016, EuroVis.

First results on the application of the Fynesse control architecture

Martin Spott, Martin A. Riedmiller, Martin Riedmiller, 1997, 1997 IEEE Aerospace Conference.

An Algorithm for Anticipating Future Decision Trees from Concept-Drifting Data

Rudolf Kruse, Martin Spott, Mirko Böttcher, 2008, SGAI Conf..

Fuzzy-neuro-controlled verified instruction scheduler

Martin Spott, Martin A. Riedmiller, Thilo S. Gaul, 1999, 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397).

Efficient Reasoning with Fuzzy Words

Martin Spott, 2002, FSKD.

Visualising Temporal Item Sets: Guided Drill-Down with Hierarchical Attributes

Martin Spott, Fabian Schmidt, 2012, SMPS.

Towards Combining Attribute-based and Time Series-based Visual Querying

Detlef D. Nauck, Martin Spott, Jürgen Bernard, 2016, EuroVis.

Intelligent data analysis with fuzzy decision trees

Rudolf Kruse, Detlef D. Nauck, Martin Spott, 2007, Soft Comput..

Feature relevance in physiological networks for classification of obstructive sleep apnea

Martin Spott, Thomas Penzel, Dagmar Krefting, 2018, Physiological measurement.

Combining fuzzy words

Martin Spott, M. Spott, 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

SPIDA — A Novel Data Analysis Tool

Detlef Nauck, Martin Spott, Ben Azvine, 2003 .

Visual Analytics as End-User Programming

Alan F. Blackwell, Martin Spott, Mateja Jamnik, 2015 .

Design of autonomously learning controllers using FYNESSE

Martin Spott, Martin A. Riedmiller, Martin Riedmiller, 2001 .

Visual-Interactive Exploration of Relations Between Time-Oriented Data and Multivariate Data

Martin Spott, Jürgen Bernard, Jörn Kohlhammer, 2016, EuroVA@EuroVis.

Interaction with Uncertainty in Visualisations

Alan F. Blackwell, Martin Spott, Mateja Jamnik, 2015, EuroVis.

Mining changing customer segments in dynamic markets

Rudolf Kruse, Detlef D. Nauck, Martin Spott, 2009, Expert Syst. Appl..

Towards a Framework for Change Detection in Data Sets

Detlef D. Nauck, Martin Spott, Dymitr Ruta, 2006, SGAI Conf..

Fuzzy methods for automated intelligent data analysis

Detlef D. Nauck, Martin Spott, Ben Azvine, 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

Towards the automation of intelligent data analysis

Detlef D. Nauck, Martin Spott, 2006, Appl. Soft Comput..

Predictive Customer Analytics and Real-Time Business Intelligence

Detlef Nauck, Martin Spott, Dymitr Ruta, 2008 .