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» Evaluating algorithms that learn from data streams
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ENC
2006
IEEE
15 years 10 months ago
Cleaning Training-Datasets with Noise-Aware Algorithms
We introduce a novel learning algorithm for noise elimination. Our algorithm is based on the re-measurement idea for the correction of erroneous observations and is able to discri...
H. Jair Escalante
BMCBI
2010
174views more  BMCBI 2010»
15 years 4 months ago
The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based h
Background: To further understand the implementation of hyperparameters re-estimation technique in Bayesian hierarchical model, we added two more prior assumptions over the weight...
Junbai Wang
IJCAI
1989
15 years 5 months ago
Noise-Tolerant Instance-Based Learning Algorithms
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
David W. Aha, Dennis F. Kibler
ICDM
2003
IEEE
220views Data Mining» more  ICDM 2003»
15 years 10 months ago
Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
PERCOM
2007
ACM
16 years 4 months ago
Energy-Efficient Data Dissemination for Wireless Sensor Networks
In order to disseminate a large amount of data through a sensor network, it is common to split the data into smallsized chunk packets. If the data is additionally encoded by a for...
Marcel Busse, Thomas Haenselmann, Wolfgang Effelsb...