Browsing by Author "Holmes, Geoffrey"

• Adaptive random forests for evolving data stream classification 

  Gomes, Heitor Murilo; Bifet, Albert; Read, Jesse; Barddal, Jean Paul; Enembreck, Fabrício; Pfahringer, Bernhard; Holmes, Geoffrey; Abdessalem, Talel (Springer, 2017)

  Random forests is currently one of the most used machine learning algorithms in the non-streaming (batch) setting. This preference is attributable to its high learning performance and low demands with respect to input ...

  

• Algorithm selection on data streams 

  van Rijn, Jan N.; Holmes, Geoffrey; Pfahringer, Bernhard; Vanschoren, Joaquin (Springer International Publishing, 2014)

  We explore the possibilities of meta-learning on data streams, in particular algorithm selection. In a first experiment we calculate the characteristics of a small sample of a data stream, and try to predict which classifier ...

  

• Analysing chromatographic data using data mining to monitor petroleum content in water 

  Holmes, Geoffrey; Fletcher, Dale; Reutemann, Peter; Frank, Eibe (Springer, 2009)

  Chromatography is an important analytical technique that has widespread use in environmental applications. A typical application is the monitoring of water samples to determine if they contain petroleum. These tests are ...

  

• An application of data mining to fruit and vegetable sample identification using Gas Chromatography-Mass Spectrometry 

  Holmes, Geoffrey; Fletcher, Dale; Reutemann, Peter (iEMSs, 2012)

  One of the uses of Gas Chromatography-Mass Spectrometry (GC-MS) is in the detection of pesticide residues in fruit and vegetables. In a high throughput laboratory there is the potential for sample swaps or mislabelling, ...

  

• Batch-Incremental Learning for Mining Data Streams 

  Holmes, Geoffrey; Kirkby, Richard Brendon; Bainbridge, David (University of Waikato, 2004)

  The data stream model for data mining places harsh restrictions on a learning algorithm. First, a model must be induced incrementally. Second, processing time for instances must keep up with their speed of arrival. Third, ...

  

• Speech analysis and synthesis using an auditory model 

  Carnegie, Dale A. (The University of Waikato, 2000)

  Many traditional speech analysis/synthesis techniques are designed to produce speech with a spectrum that is as close as possible to the original. This may not be necessary because the auditory nerve is the only link from ...

  

• High-throughput machine learning algorithms 

  Mitchell, Rory (The University of Waikato, 2021)

  The field of machine learning has become strongly compute driven, such that emerging research and applications require larger amounts of specialised hardware or smarter algorithms to advance beyond the state-of-the-art. ...

  

• Tree-structured multiclass probability estimators 

  Leathart, Timothy Matthew (The University of Waikato, 2019)

  Nested dichotomies are used as a method of transforming a multiclass classification problem into a series of binary problems. A binary tree structure is constructed over the label space that recursively splits the set of ...

  

• Reconstructing Data Provenance from Log Files 

  Tan, Yu Shyang (The University of Waikato, 2017)

  Data provenance describes the derivation history of data, capturing details such as the entities involved and the relationships between entities. Knowledge of data provenance can be used to address issues, such as data ...

  

• Distributed Operating Systems on Wireless Sensor Networks 

  Hunkin, Paul Wade (University of Waikato, 2017)

  This thesis proposes the use of traditional distributed operating system and distributed systems techniques that are adapted and applied to the wireless sensor network domain. These techniques are applied to the creation ...

  

... View More