title: Having a Blast: Meta-Learning and Heterogeneous Ensembles for Data Streams

authors: van Rijn, Jan N.

subjects: Science & Technology

abstract: Ensembles of classifiers are among the best performing classifiers available in many data mining applications. However, most ensembles developed specifically for the dynamic data stream setting rely on only one type of base-level classifier, most often Hoeffding Trees. In this paper, we study the use of heterogeneous ensembles, comprised of fundamentally different model types. Heterogeneous ensembles have proven successful in the classical batch data setting, however they do not easily transfer to the data stream setting. We therefore introduce the Online Performance Estimation framework, which can be used in data stream ensembles to weight the votes of (heterogeneous) ensemble members differently across the stream. Experiments over a wide range of data streams show performance that is competitive with state of the art ensemble techniques, including Online Bagging and Leveraging Bagging. All experimental results from this work are easily reproducible and publicly available on OpenML for further analysis.

text: Having a Blast: Meta-Learning and Heterogeneous Ensembles for Data Streams Ensembles of classifiers are among the best performing classifiers available in many data mining applications. However, most ensembles developed specifically for the dynamic data stream setting rely on only one type of base-level classifier, most often Hoeffding Trees. In this paper, we study the use of heterogeneous ensembles, comprised of fundamentally different model types. Heterogeneous ensembles have proven successful in the classical batch data setting, however they do not easily transfer to the data stream setting. We therefore introduce the Online Performance Estimation framework, which can be used in data stream ensembles to weight the votes of (heterogeneous) ensemble members differently across the stream. Experiments over a wide range of data streams show performance that is competitive with state of the art ensemble techniques, including Online Bagging and Leveraging Bagging. All experimental results from this work are easily reproducible and publicly available on OpenML for further analysis.

year: 2015-01-01

title: Influences of indication response requirement and target prevalence on dogs’ performance in a scent-detection task

authors: Edwards, Timothy L.

abstract: Scent-detection dogs assist humans with many socially significant tasks and hold promise for assisting with many others. However, the methods used to train scent-detection dogs and the conditions under which they work are highly variable, and the influences of many relevant factors on scent-detection performance are poorly understood. Using an automated scent-detection apparatus that allowed the dogs to work independently from a handler, we evaluated the influence of two factors on scent-detection performance with amyl acetate as the target. In the first experiment in this study, we examined the influence of the indication response requirement on the performance of five dogs trained to perform a scent-detection task. The indication response consisted of the dogs breaking an infrared beam in a port through which they accessed samples. The response requirement was manipulated by adjusting the duration of the beam break that was required to activate food reinforcement if the target was present. As the indication response requirement increased, dogs’ ability to detect the target remained unchanged, as indicated by stable log d measures across durations (p =.09), but their response bias, represented by log B, shifted from a tendency to indicate that targets were present to a tendency to indicate that targets were absent (p <.001). In the second experiment, we examined the influence of target prevalence, or the proportion of samples that are target samples, on four dogs’ scent-detection performance. As target prevalence decreased, the dogs’ ability to detect the target remained unchanged (p =.13), but their response bias shifted from a tendency to indicate that the targets were present to a tendency to indicate that targets were absent (p <.001). This finding aligns with the “low-prevalence effect,” which is commonly observed in human signal detection research. The findings from both experiments have important theoretical and practical implications. For example, by adjusting response effort, we can alter dogs’ response bias toward or away from indicating the presence of targets and, by having a clear understanding of the influence of target prevalence on bias, we can make informed decisions about the need to artificially increase target prevalence when dogs are searching for rare targets.

text: Influences of indication response requirement and target prevalence on dogs’ performance in a scent-detection task Scent-detection dogs assist humans with many socially significant tasks and hold promise for assisting with many others. However, the methods used to train scent-detection dogs and the conditions under which they work are highly variable, and the influences of many relevant factors on scent-detection performance are poorly understood. Using an automated scent-detection apparatus that allowed the dogs to work independently from a handler, we evaluated the influence of two factors on scent-detection performance with amyl acetate as the target. In the first experiment in this study, we examined the influence of the indication response requirement on the performance of five dogs trained to perform a scent-detection task. The indication response consisted of the dogs breaking an infrared beam in a port through which they accessed samples. The response requirement was manipulated by adjusting the duration of the beam break that was required to activate food reinforcement if the target was present. As the indication response requirement increased, dogs’ ability to detect the target remained unchanged, as indicated by stable log d measures across durations (p =.09), but their response bias, represented by log B, shifted from a tendency to indicate that targets were present to a tendency to indicate that targets were absent (p <.001). In the second experiment, we examined the influence of target prevalence, or the proportion of samples that are target samples, on four dogs’ scent-detection performance. As target prevalence decreased, the dogs’ ability to detect the target remained unchanged (p =.13), but their response bias shifted from a tendency to indicate that the targets were present to a tendency to indicate that targets were absent (p <.001). This finding aligns with the “low-prevalence effect,” which is commonly observed in human signal detection research. The findings from both experiments have important theoretical and practical implications. For example, by adjusting response effort, we can alter dogs’ response bias toward or away from indicating the presence of targets and, by having a clear understanding of the influence of target prevalence on bias, we can make informed decisions about the need to artificially increase target prevalence when dogs are searching for rare targets.

year: 2022

title: Putting it in there: "PSYC575 Indigenous Psychologies" as a for-credit university paper in New Zealand

authors: Waitoki, Waikaremoana

abstract: Over the past 30 years, scholar advocates have sparked the emergence of indigenous psychology as an important contribution to understanding the experiences and challenges faced by indigenous peoples. Part of this exercise is to also bring indigenous knowledges to the learning table as critical information for meaning making and resolving psychological challenges. Increasingly, academics are writing and teaching papers in the fledgling field as important and legitimate contributions for undergraduate and graduate degree credit. Previously, students and academics were confined to the more flexible research driven, directed-learning, study options rather than papers explicitly advertised and institutionally promoted. In this paper, we discuss how we are going about writing the curricula for a graduate level paper called "Indigenous Psychologies" to be offered in 2016 at the University of Waikato, New Zealand. We discuss a) principles that guide curricula decision-making; b) the programme of lecture topics developed; and c) finding and developing supporting resources. We welcome conversation and resource sharing.

text: Putting it in there: "PSYC575 Indigenous Psychologies" as a for-credit university paper in New Zealand Over the past 30 years, scholar advocates have sparked the emergence of indigenous psychology as an important contribution to understanding the experiences and challenges faced by indigenous peoples. Part of this exercise is to also bring indigenous knowledges to the learning table as critical information for meaning making and resolving psychological challenges. Increasingly, academics are writing and teaching papers in the fledgling field as important and legitimate contributions for undergraduate and graduate degree credit. Previously, students and academics were confined to the more flexible research driven, directed-learning, study options rather than papers explicitly advertised and institutionally promoted. In this paper, we discuss how we are going about writing the curricula for a graduate level paper called "Indigenous Psychologies" to be offered in 2016 at the University of Waikato, New Zealand. We discuss a) principles that guide curricula decision-making; b) the programme of lecture topics developed; and c) finding and developing supporting resources. We welcome conversation and resource sharing.

year: 2015