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Decision Trees

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Development of prediction software to describe total mesophilic bacteria in spinach using a machine learning-based regression approach.

Food science and technology international = Ciencia y tecnologia de los alimentos internacional
The purpose of this study was to create a tool for predicting the growth of total mesophilic bacteria in spinach using machine learning-based regression models such as support vector regression, decision tree regression, and Gaussian process regressi...

Gender classification from anthropometric measurement by boosting decision tree: A novel machine learning approach.

Journal of the National Medical Association
The decision tree used a generating set of rules based on various correlated variables for developing an algorithm from the target variable. Using the training dataset this paper used boosting tree algorithm for gender classification from twenty-five...

Neural network and decision tree-based machine learning tools to analyse the anion-responsive behaviours of emissive Ru(II)-terpyridine complexes.

Dalton transactions (Cambridge, England : 2003)
We implemented both neural network and decision tree-based machine learning tools to analyse the anion-responsive behaviours of two heteroleptic Ru(II) complexes based on two tridentate ligands, 2,6-bis(benzimidazole-2-yl)pyridine (Hpbbzim) and subst...

A Machine Learning Model for Prediction of Amputation in Diabetics.

Journal of diabetes science and technology
BACKGROUND: Diabetic foot ulcer (DFU) and the resulting lower extremity amputation are associated with a poor survival prognosis. The objective of this study is to generate a model for predicting the probability of major amputation in hospitalized pa...

Text Analysis of Radiology Reports with Signs of Intracranial Hemorrhage on Brain CT Scans Using the Decision Tree Algorithm.

Sovremennye tekhnologii v meditsine
UNLABELLED: is to create, train, and test the algorithm for the analysis of brain CT text reports using a decision tree model to solve the task of simple binary classification of presence/absence of intracranial hemorrhage (ICH) signs.

Construction of College Chinese Blended Teaching Mode Based on Decision Tree Classification Model in New Media Context.

Computational intelligence and neuroscience
Based on the context of new media and big data, this article uses the decision tree classification model to construct the college Chinese hybrid teaching mode. In order to verify the accuracy of ID3 algorithm prediction, the comparison of the ID3 alg...

Using Decision Tree Classification and AdaBoost Classification to Build the Abnormal Data Monitoring System of Financial Accounting in Colleges and Universities.

Computational intelligence and neuroscience
In order to better solve the problems of low efficiency, large consumption of human resources, and relatively low degree of intelligence in the abnormal data monitoring system of financial accounting in colleges and universities under the background ...

Diagnosis of Early Glottic Cancer Using Laryngeal Image and Voice Based on Ensemble Learning of Convolutional Neural Network Classifiers.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: The purpose of study is to improve the classification accuracy by comparing the results obtained by applying decision tree ensemble learning, which is one of the methods to increase the classification accuracy for a relatively small datas...

Decision-Tree-Initialized Dendritic Neuron Model for Fast and Accurate Data Classification.

IEEE transactions on neural networks and learning systems
This work proposes a decision tree (DT)-based method for initializing a dendritic neuron model (DNM). Neural networks become larger and larger, thus consuming more and more computing resources. This calls for a strong need to prune neurons that do no...

Comparison of machine learning methods for the detection of focal cortical dysplasia lesions: decision tree, support vector machine and artificial neural network.

Neurological research
BACKGROUND: Accurate classification of focal cortical dysplasia (FCD) has been challenging due to the problematic visual detection in magnetic resonance imaging (MRI). Hence, recently, there has been a necessity for employing new techniques to solve ...