Results 51 to 60 of about 1,054,775 (163)
An application of decision trees method for fault diagnosis of induction motors [PDF]
, 2006 Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine learning, pattern recognition, and data mining have considered the decision tree ...
Oh, Myung-Suck +2 more
core
Efficient algorithms for decision tree cross-validation
, 2001 Cross-validation is a useful and generally applicable technique often employed in machine learning, including decision tree induction. An important disadvantage of straightforward implementation of the technique is its computational overhead.
Blockeel, Hendrik, Struyf, Jan
core +4 more sources
Multi-test Decision Tree and its Application to Microarray Data Classification [PDF]
, 2014 Objective: The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the ...
Armstrong +46 more
core +1 more source
Greedy Algorithm for Deriving Decision Rules from Decision Tree Ensembles
EntropyThis study introduces a greedy algorithm for deriving decision rules from decision tree ensembles, targeting enhanced interpretability and generalization in distributed data environments.
Evans Teiko Tetteh, Beata Zielosko
doaj +1 more source
On Laws of Thought—A Quantum-like Machine Learning Approach
Entropy, 2023 Incorporating insights from quantum theory, we propose a machine learning-based decision-making model, including a logic tree and a value tree; a genetic programming algorithm is applied to optimize both the logic tree and value tree.
Lizhi Xin, Kevin Xin, Houwen Xin
doaj +1 more source
Hyperparameter Optimization Using Iterative Decision Tree (IDT)
IEEE Access, 2022 Machine learning and deep learning have gained a lot of attention from researchers because of their promising predictive performance and the availability of extensive high-dimensional data and high-performance computational hardware.
Narith Saum +2 more
doaj +1 more source
, 2015 In order to speed-up classification models when facing a large number of categories, one usual approach consists in organizing the categories in a particular structure, this structure being then used as a way to speed-up the prediction computation. This is for example the case when using error-correcting codes or even hierarchies of categories.
Léon, Aurélia, Denoyer, Ludovic
openaire +3 more sources
Decision Tree Algorithm Considering Distances Between Classes
IEEE Access, 2022 Decision tree algorithm (DT) is a commonly used data mining method for classification and regression. DT repeatedly divides a dataset into pure subsets based on impurity measurements such as entropy and Gini.
Sangyong Lee +3 more
doaj +1 more source
Engineering and Applied Science Research, 2022 Decision Trees are a common approach used for classifying unseen data into defined classes. The Information Gain is usually applied as splitting criteria in the node selection process for constructing the decision tree.
Sirichanya Chanmee, Kraisak Kesorn
doaj
Extension of Decision Tree Algorithm for Stream Data Mining Using Real Data [PDF]
, 2009 Recently, because of increasing amount of data in the society, data stream mining targeting large scale data has attracted attention. The data mining is a technology of discovery new knowledge and patterns from the massive amounts of data, and what the ...
Ise, Masayuki +3 more
core