title: The need for open source software in machine learning

authors: Sonnenburg, Soren

subjects: machine learning

abstract: Open source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for diverse applications. However, the true potential of these methods is not used, since existing implementations are not openly shared, resulting in software with low usability, and weak interoperability. We argue that this situation can be significantly improved by increasing incentives for researchers to publish their software under an open source model. Additionally, we outline the problems authors are faced with when trying to publish algorithmic implementations of machine learning methods. We believe that a resource of peer reviewed software accompanied by short articles would be highly valuable to both the machine learning and the general scientific community.

text: The need for open source software in machine learning Open source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for diverse applications. However, the true potential of these methods is not used, since existing implementations are not openly shared, resulting in software with low usability, and weak interoperability. We argue that this situation can be significantly improved by increasing incentives for researchers to publish their software under an open source model. Additionally, we outline the problems authors are faced with when trying to publish algorithmic implementations of machine learning methods. We believe that a resource of peer reviewed software accompanied by short articles would be highly valuable to both the machine learning and the general scientific community.

year: 2007

title: Combining Naive Bayes and Decision Tables

authors: Hall, Mark A.

subjects: computer science

abstract: We investigate a simple semi-naive Bayesian ranking method that combine naive Bayes with induction of decision tables. Naive Bayes and decision tables can both be trained efficientyly, and the same holds true for the combined semi-naive model. We show that the resulting ranker, compared to either component technique, frequently significantly increases AUC. For some datasets it significantly improves on both techniques. This is also the case when attribute selection is performed in naive Bayes and its semi-naive variant.

text: Combining Naive Bayes and Decision Tables We investigate a simple semi-naive Bayesian ranking method that combine naive Bayes with induction of decision tables. Naive Bayes and decision tables can both be trained efficientyly, and the same holds true for the combined semi-naive model. We show that the resulting ranker, compared to either component technique, frequently significantly increases AUC. For some datasets it significantly improves on both techniques. This is also the case when attribute selection is performed in naive Bayes and its semi-naive variant.

year: 2008

title: Listening to the voices of Year 13 Māori students: A case study in a New Zealand secondary school

authors: Kay, Joan-Marie

subjects: Maori Achievement

abstract: This research focuses on listening to the voices of Year 13 academically successful Māori students in a large, urban, mainstream, co-educational, decile 4, New Zealand secondary school. Traditionally, researchers have tended to emphasise the poor academic performance of Māori students in New Zealand. In contrast, this qualitative case study, however, seeks to understand what influences and motivates the academically successful Year 13 Māori students who have gained the National Certificate of Educational Achievement (NCEA) Level 2 and who returned to school to study for NCEA Level 3.

Semi structured interviews as conversations with all thirteen Māori students who had achieved NCEA Level 2 formed the basis of this research. Five of their parents, seven of their teachers and the principal were also interviewed.

The findings show that these students all stress the importance of their family, in particular, one family member or significant adult in their lives who valued education and supported the student, influencing and encouraging their motivation and self-efficacy. Building positive relationships with their teachers was the next strongest influence on their academic success followed closely by the positive influence of their friends. Self-motivation was mainly extrinsic. The students perceived that the principal had little effect on their individual achievement.

The teachers also acknowledge the importance of building positive relationships with their students and acknowledge the benefits of the reflective practice provided by the Te Kotahitanga project in highlighting this factor.

The findings suggest the excellent initiatives currently taking place in the school need to be continued or strengthened and that further interventions which target particular Māori students, rather than are global across the school, should be introduced.

text: Listening to the voices of Year 13 Māori students: A case study in a New Zealand secondary school This research focuses on listening to the voices of Year 13 academically successful Māori students in a large, urban, mainstream, co-educational, decile 4, New Zealand secondary school. Traditionally, researchers have tended to emphasise the poor academic performance of Māori students in New Zealand. In contrast, this qualitative case study, however, seeks to understand what influences and motivates the academically successful Year 13 Māori students who have gained the National Certificate of Educational Achievement (NCEA) Level 2 and who returned to school to study for NCEA Level 3.

Semi structured interviews as conversations with all thirteen Māori students who had achieved NCEA Level 2 formed the basis of this research. Five of their parents, seven of their teachers and the principal were also interviewed.

The findings show that these students all stress the importance of their family, in particular, one family member or significant adult in their lives who valued education and supported the student, influencing and encouraging their motivation and self-efficacy. Building positive relationships with their teachers was the next strongest influence on their academic success followed closely by the positive influence of their friends. Self-motivation was mainly extrinsic. The students perceived that the principal had little effect on their individual achievement.

The teachers also acknowledge the importance of building positive relationships with their students and acknowledge the benefits of the reflective practice provided by the Te Kotahitanga project in highlighting this factor.

The findings suggest the excellent initiatives currently taking place in the school need to be continued or strengthened and that further interventions which target particular Māori students, rather than are global across the school, should be introduced.

year: 2008