220 search results - page 3 / 44 » Learning to Classify Text from Labeled and Unlabeled Documen... |
KDD
2008
ACM
14 years 5 months ago
2008
ACM
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify te...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
CICLING
2004
Springer
13 years 10 months ago
2004
Springer
When text categorization is applied to complex tasks, it is tedious and expensive to hand-label the large amounts of training data necessary for good performance. In this paper, we...