Add to ORKGAbstract. We introduce a new method for building classification models when we have prior knowledge of how the classes can be arranged in a hierarchy, based on how easily they can be distinguished. The new method uses a Bayesian form of the multinomial logit (MNL, a.k.a. “softmax”) model, with a prior that introduces correlations between the parameters for classes that are nearby in the tree. We compare the performance on simulated data of the new method, the ordinary MNL model, and a model that uses the hierarchy in different way. We also test the new method on a document labelling problem, and find that it performs better than the other methods, particularly when the amount of training data is small.
Hierarchical classes models are models for N-way N-mode data that represent the association among th...
In classification problems, especially those that categorize data into a large number of classes, th...
We study the problem of hierarchical classification when labels corresponding to partial and/or mult...
This paper proposes a way of improving classification performance for classes which have very few tr...
A challenging problem in hierarchical classification is to leverage the hierarchi-cal relations amon...
<p>A challenging problem in hierarchical classification is to leverage the hierarchical relations am...
We employed a multilevel hierarchical Bayesian model in the task of exploiting relevant interactions...
Categories are often organized into hierarchical taxonomies, that is, tree structures where each nod...
Trees are a common way of organizing large amounts of information by placing items with similar ch...
In many real world datasets, we seek to make predictions about entities, where the entities are in c...
Decision Tree classifier builds a classification model using training data. It consists of records h...
Abstract Background We investigate whether annotation...
BackgroundWe investigate whether annotation of gene function can be improved using a classification ...
We study hierarchical classification in the general case when an instance could belong to more than ...
We study the problem of hierarchical classification when labels corre-sponding to partial and/or mul...
Hierarchical classes models are models for N-way N-mode data that represent the association among th...
In classification problems, especially those that categorize data into a large number of classes, th...
We study the problem of hierarchical classification when labels corresponding to partial and/or mult...
This paper proposes a way of improving classification performance for classes which have very few tr...
A challenging problem in hierarchical classification is to leverage the hierarchi-cal relations amon...
<p>A challenging problem in hierarchical classification is to leverage the hierarchical relations am...
We employed a multilevel hierarchical Bayesian model in the task of exploiting relevant interactions...
Categories are often organized into hierarchical taxonomies, that is, tree structures where each nod...
Trees are a common way of organizing large amounts of information by placing items with similar ch...
In many real world datasets, we seek to make predictions about entities, where the entities are in c...
Decision Tree classifier builds a classification model using training data. It consists of records h...
Abstract Background We investigate whether annotation...
BackgroundWe investigate whether annotation of gene function can be improved using a classification ...
We study hierarchical classification in the general case when an instance could belong to more than ...
We study the problem of hierarchical classification when labels corre-sponding to partial and/or mul...
Hierarchical classes models are models for N-way N-mode data that represent the association among th...
In classification problems, especially those that categorize data into a large number of classes, th...
We study the problem of hierarchical classification when labels corresponding to partial and/or mult...