title: Designing similarity functions

authors: Trigg, Leonard E.

abstract: The concept of similarity is important in many areas of cognitive science, computer science, and statistics. In machine learning, functions that measure similarity between two instances form the core of instance-based classifiers. Past similarity measures have been primarily based on simple Euclidean distance. As machine learning has matured, it has become obvious that a simple numeric instance representation is insufficient for most domains. Similarity functions for symbolic attributes have been developed, and simple methods for combining these functions with numeric similarity functions were devised. This sequence of events has revealed three important issues, which this thesis addresses.

The first issue is concerned with combining multiple measures of similarity. There is no equivalence between units of numeric similarity and units of symbolic similarity. Existing similarity functions for numeric and symbolic attributes have no common foundation, and so various schemes have been devised to avoid biasing the overall similarity towards one type of attribute. The similarity function design framework proposed by this thesis produces probability distributions that describe the likelihood of transforming between two attribute values. Because common units of probability are employed, similarities may be combined using standard methods. It is empirically shown that the resulting similarity functions treat different attribute types coherently.

The second issue relates to the instance representation itself. The current choice of numeric and symbolic attribute types is insufficient for many domains, in which more complicated representations are required. For example, a domain may require varying numbers of features, or features with structural information. The framework proposed by this thesis is sufficiently general to permit virtually any type of instance representation-all that is required is that a set of basic transformations that operate on the instances be defined. To illustrate the framework’s applicability to different instance representations, several example similarity functions are developed. 

The third, and perhaps most important, issue concerns the ability to incorporate domain knowledge within similarity functions. Domain information plays an important part in choosing an instance representation. However, even given an adequate instance representation, domain information is often lost. For example, numeric features that are modulo (such as the time of day) can be perfectly represented as a numeric attribute, but simple linear similarity functions ignore the modulo nature of the attribute. Similarly, symbolic attributes may have inter-symbol relationships that should be captured in the similarity function. The design framework proposed by this thesis allows domain information to be captured in the similarity function, both in the transformation model and in the probability assigned to basic transformations. Empirical results indicate that such domain information improves classifier performance, particularly when training data is limited.

text: Designing similarity functions The concept of similarity is important in many areas of cognitive science, computer science, and statistics. In machine learning, functions that measure similarity between two instances form the core of instance-based classifiers. Past similarity measures have been primarily based on simple Euclidean distance. As machine learning has matured, it has become obvious that a simple numeric instance representation is insufficient for most domains. Similarity functions for symbolic attributes have been developed, and simple methods for combining these functions with numeric similarity functions were devised. This sequence of events has revealed three important issues, which this thesis addresses.

The first issue is concerned with combining multiple measures of similarity. There is no equivalence between units of numeric similarity and units of symbolic similarity. Existing similarity functions for numeric and symbolic attributes have no common foundation, and so various schemes have been devised to avoid biasing the overall similarity towards one type of attribute. The similarity function design framework proposed by this thesis produces probability distributions that describe the likelihood of transforming between two attribute values. Because common units of probability are employed, similarities may be combined using standard methods. It is empirically shown that the resulting similarity functions treat different attribute types coherently.

The second issue relates to the instance representation itself. The current choice of numeric and symbolic attribute types is insufficient for many domains, in which more complicated representations are required. For example, a domain may require varying numbers of features, or features with structural information. The framework proposed by this thesis is sufficiently general to permit virtually any type of instance representation-all that is required is that a set of basic transformations that operate on the instances be defined. To illustrate the framework’s applicability to different instance representations, several example similarity functions are developed. 

The third, and perhaps most important, issue concerns the ability to incorporate domain knowledge within similarity functions. Domain information plays an important part in choosing an instance representation. However, even given an adequate instance representation, domain information is often lost. For example, numeric features that are modulo (such as the time of day) can be perfectly represented as a numeric attribute, but simple linear similarity functions ignore the modulo nature of the attribute. Similarly, symbolic attributes may have inter-symbol relationships that should be captured in the similarity function. The design framework proposed by this thesis allows domain information to be captured in the similarity function, both in the transformation model and in the probability assigned to basic transformations. Empirical results indicate that such domain information improves classifier performance, particularly when training data is limited.

year: 1997

title: Timing of reinforcement during dog training

authors: Browne, Clare Melody

subjects: training

abstract: Research on dog-human communication has demonstrated that dogs are extremely responsive to human cues such as pointing, eye gazing and vocalizations. Because dogs are so receptive to such cues, it is reasonable to assume that subtle feedback from humans has an effect on the efficacy of dog training. Timing of reinforcement in the field of dog behavior has not been researched extensively. Research on other species has demonstrated that although animals can learn tasks with delays to reinforcement, longer delays result in longer average times to task acquisition and relatively lower rates of responding. The aim of this study was to examine owners’ latencies to providing reinforcers for their dogs’ responses during basic dog training. Video observations were made at three New Zealand dog obedience clubs. Fifteen people volunteered to take part in this study with their dogs. All participants were members of beginner classes and were videoed while training their dogs in class. Behaviors appropriate for examining the timing of reinforcement required a clearly-definable start and finish point, so ‘sit’ and ‘down’ were chosen for analysis. Times were measured between the owners’ commands, the dogs’ responses, secondary reinforcement (verbal praise), and primary reinforcement (food).
Preliminary analysis of data from seven participants shows that dogs were reinforced for responding correctly to 27% of commands. These events were used for timing analysis. In addition, the dogs responded correctly but received no reinforcer of any type for 31% of commands, they responded incorrectly to 2% of commands and 40% of commands elicited no response from the dogs. There was considerable variation across participants’ timing of reinforcement with the latency to deliver the first instance of reinforcement (secondary or primary) ranging from 0 to > 5 seconds. No significant difference was found between owners’ latency to deliver secondary or primary reinforcement (t (5) = −1.66, P = 0.16) or between the times taken to reinforce ‘sit’ or ‘down’ responses (t (5) = −0.65, P = 0.54) (first instance of reinforcement). Results showed a positive correlation between the time to the first instance of reinforcement and the proportion of incorrect responses (r (7) = 0.65, P = 0.12).
We conclude that given the wide range of latencies to reinforcement, it is possible that the dogs’ task acquisition was suboptimal at times. Delays to reinforcement may also give room for unintentional feedback to occur, particularly as dogs are so receptive to human-given cues. Ongoing research will attempt to address these questions.

text: Timing of reinforcement during dog training Research on dog-human communication has demonstrated that dogs are extremely responsive to human cues such as pointing, eye gazing and vocalizations. Because dogs are so receptive to such cues, it is reasonable to assume that subtle feedback from humans has an effect on the efficacy of dog training. Timing of reinforcement in the field of dog behavior has not been researched extensively. Research on other species has demonstrated that although animals can learn tasks with delays to reinforcement, longer delays result in longer average times to task acquisition and relatively lower rates of responding. The aim of this study was to examine owners’ latencies to providing reinforcers for their dogs’ responses during basic dog training. Video observations were made at three New Zealand dog obedience clubs. Fifteen people volunteered to take part in this study with their dogs. All participants were members of beginner classes and were videoed while training their dogs in class. Behaviors appropriate for examining the timing of reinforcement required a clearly-definable start and finish point, so ‘sit’ and ‘down’ were chosen for analysis. Times were measured between the owners’ commands, the dogs’ responses, secondary reinforcement (verbal praise), and primary reinforcement (food).
Preliminary analysis of data from seven participants shows that dogs were reinforced for responding correctly to 27% of commands. These events were used for timing analysis. In addition, the dogs responded correctly but received no reinforcer of any type for 31% of commands, they responded incorrectly to 2% of commands and 40% of commands elicited no response from the dogs. There was considerable variation across participants’ timing of reinforcement with the latency to deliver the first instance of reinforcement (secondary or primary) ranging from 0 to > 5 seconds. No significant difference was found between owners’ latency to deliver secondary or primary reinforcement (t (5) = −1.66, P = 0.16) or between the times taken to reinforce ‘sit’ or ‘down’ responses (t (5) = −0.65, P = 0.54) (first instance of reinforcement). Results showed a positive correlation between the time to the first instance of reinforcement and the proportion of incorrect responses (r (7) = 0.65, P = 0.12).
We conclude that given the wide range of latencies to reinforcement, it is possible that the dogs’ task acquisition was suboptimal at times. Delays to reinforcement may also give room for unintentional feedback to occur, particularly as dogs are so receptive to human-given cues. Ongoing research will attempt to address these questions.

year: 2011

title: Investigating commentary on the fifth labour-led government’s third way approach

authors: Piercy, Gemma Louise

abstract: After the 1999 election of a Labour-led coalition government in Aotearoa New Zealand, a raft of policy reforms adopted characteristics of the ‘Third Way’ ideology promoted by Anthony Giddens. We argue, however, that Third Way characteristics were not implemented in Aotearoa New Zealand without attracting criticism. This article reviews academic analysis and wider commentary on the Third Way in Aotearoa New Zealand, much of which particularly focused on social policy reforms made by the Labour-led coalition government (1999-2008). We have used this literature to identify the varied ways in which the Third Way was defined and the extent to which Third Way ideology was considered to have influenced policy and practice the Aotearoa New Zealand context. Our semi-systematic literature review shows that many commentators argued that New Zealand did indeed implement a policy platform consistent with Third Way ideological characteristics but these were also adapted to the unique context of Aotearoa New Zealand. We explore in detail two key examples of adaptation di scussed in the literature: the Labour-led government’s early focus on reducing inequalities between Māori and non-Māori and on renewing civil society through subsidiarity and a partnership approach.

text: Investigating commentary on the fifth labour-led government’s third way approach After the 1999 election of a Labour-led coalition government in Aotearoa New Zealand, a raft of policy reforms adopted characteristics of the ‘Third Way’ ideology promoted by Anthony Giddens. We argue, however, that Third Way characteristics were not implemented in Aotearoa New Zealand without attracting criticism. This article reviews academic analysis and wider commentary on the Third Way in Aotearoa New Zealand, much of which particularly focused on social policy reforms made by the Labour-led coalition government (1999-2008). We have used this literature to identify the varied ways in which the Third Way was defined and the extent to which Third Way ideology was considered to have influenced policy and practice the Aotearoa New Zealand context. Our semi-systematic literature review shows that many commentators argued that New Zealand did indeed implement a policy platform consistent with Third Way ideological characteristics but these were also adapted to the unique context of Aotearoa New Zealand. We explore in detail two key examples of adaptation di scussed in the literature: the Labour-led government’s early focus on reducing inequalities between Māori and non-Māori and on renewing civil society through subsidiarity and a partnership approach.

year: 2017