A Literature Review on Supervised Machine Learning Algorithms and Boosting Process

@article{Praveena2017ALR,
  title={A Literature Review on Supervised Machine Learning Algorithms and Boosting Process},
  author={M. Praveena and V. Jaiganesh},
  journal={International Journal of Computer Applications},
  year={2017},
  volume={169},
  pages={32-35}
}
Data mining is one amid the core research areas in the field of computer science. Yet there is a knowledge data detection process helps the data mining to extract hidden information from the dataset there is a big scope of machine learning algorithms. Especially supervised machine learning algorithms gain extensive importance in data mining research. Boosting action is regularly helps the supervised machine learning algorithms for rising the predictive / classification veracity. This survey… 
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References

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Cluster-Based Boosting
TLDR
This work proposes a novel cluster-based boosting (CBB) approach that boosts selectively on each cluster based on both the additional structure provided by the cluster and previous function accuracy on the member data to improve predictive accuracy on problematic training data.
Exploiting Universum data in AdaBoost using gradient descent
An one-class classification support vector machine model by interval-valued training data
AdaBoost-based artificial neural network learning
Structural nonparallel support vector machine for pattern recognition
A robust multi-class AdaBoost algorithm for mislabeled noisy data
Example-dependent cost-sensitive decision trees
Building support vector machines in the context of regularized least squares
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