A Framework for Learning from Distributed Data Using Sufficient Statistics and Its Application to Learning Decision Trees
نویسندگان
چکیده
منابع مشابه
A Framework for Learning from Distributed Data Using Sufficient Statistics and Its Application to Learning Decision Trees
This paper motivates and precisely formulates the problem of learning from distributed data; describes a general strategy for transforming traditional machine learning algorithms into algorithms for learning from distributed data; demonstrates the application of this strategy to devise algorithms for decision tree induction from distributed data; and identifies the conditions under which the al...
متن کاملDesigning a learning approach to community-based decision-making: Using analytical statistics and decision trees to optimize a data structure
This paper describes an effort to predict alumni success as measured by employer satisfaction in a veterinary medical education environment. Due to the complexity of the data, this paper sought to augment regression analysis with decision tree analysis to see if the combination of both approaches could result in new insights. Potential predictors of employer satisfaction were characterized as e...
متن کاملLearning Decision Trees From Histogram Data
When applying learning algorithms to histogram data, bins of such variables are normally treated as separate independent variables. However, this may lead to a loss of information as the underlying dependencies may not be fully exploited. In this paper, we adapt the standard decision tree learning algorithm to handle histogram data by proposing a novel method for partitioning examples using bin...
متن کاملthe relationship between using language learning strategies, learners’ optimism, educational status, duration of learning and demotivation
with the growth of more humanistic approaches towards teaching foreign languages, more emphasis has been put on learners’ feelings, emotions and individual differences. one of the issues in teaching and learning english as a foreign language is demotivation. the purpose of this study was to investigate the relationship between the components of language learning strategies, optimism, duration o...
15 صفحه اولLearning Decision Trees for Unbalanced Data
Learning from unbalanced datasets presents a convoluted problem in which traditional learning algorithms may perform poorly. The objective functions used for learning the classifiers typically tend to favor the larger, less important classes in such problems. This paper compares the performance of several popular decision tree splitting criteria – information gain, Gini measure, and DKM – and i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Hybrid Intelligent Systems
سال: 2004
ISSN: 1875-8819,1448-5869
DOI: 10.3233/his-2004-11-210