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Tree Ensembles on the induced discrete space
(Institute of Electrical and Electronics Engineers Inc., 2016-05)
Decision trees are widely used predictive models in machine learning. Recently, K-tree is proposed, where the original discrete feature space is expanded by generating all orderings of values of k discrete attributes and ...
Regularizing soft decision trees
(Springer, 2013)
Recently, we have proposed a new decision tree family called soft decision trees where a node chooses both its left and right children with different probabilities as given by a gating function, different from a hard ...
Mapping classifiers and datasets
(Pergamon-Elsevier Science Ltd, 2011-04)
Given the posterior probability estimates of 14 classifiers on 38 datasets, we plot two-dimensional maps of classifiers and datasets using principal component analysis (PCA) and Isomap. The similarity between classifiers ...
Soft decision trees
(IEEE, 2012)
We discuss a novel decision tree architecture with soft decisions at the internal nodes where we choose both children with probabilities given by a sigmoid gating function. Our algorithm is incremental where new nodes are ...
Tweet sentiment analysis for cryptocurrencies
(IEEE, 2021-10-13)
Many traders believe in and use Twitter tweets to guide their daily cryptocurrency trading. In this project, we investigated the feasibility of automated sentiment analysis for cryptocurrencies. For the study, we targeted ...