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Neural Bag-of-Features learning

Pattern Recognition, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Passalis, Nikolaos, Tefas, Anastasios
openaire   +2 more sources

Feature Construction during Tree Learning

1991
This paper addresses the “problem of new terms” in the context of learning decision trees using the approach based on ID3. We discuss an algorithm for efficiently constructing new features from given primitive features and relate it to constructive induction.
Gerhard Mehlsam   +2 more
openaire   +1 more source

Adaptation? Learning? Features of biological learning

2012 International Symposium on Micro-NanoMechatronics and Human Science (MHS), 2012
All living organisms can learn the behavior appropriate to the environment. The learning process is, however, seems to be the convergence to the adapted behavior rather than learning. Living organisms can create the appropriate behavior through the behavior control in the environment.
openaire   +1 more source

Causal Feature Learning

SSRN Electronic Journal, 2022
Iman A. Wahle   +2 more
openaire   +1 more source

Feature Learning

2020
David Zhang, Kebin Wu
openaire   +1 more source

Unsupervised Feature Selection via Controllable Adaptive Graph Learning and Discriminative Feature Learning

IEEE Transactions on Neural Networks and Learning Systems
Unsupervised feature selection is challenging in machine learning, pattern recognition, and data mining. The crucial difficulty is to learn a moderate subspace that preserves the intrinsic structure and to find uncorrelated or independent features simultaneously.
Pei Huang, Mengying Xie, Xiaowei Yang
openaire   +2 more sources

Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce   +2 more
exaly  

Human Feature Learning

2012
Joseph L. Austerweil   +1 more
openaire   +2 more sources

Features section: Problem-based learning

Biochemical Education, 1993
openaire   +1 more source

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