Predictive Toxicology: Modeling Chemical Induced Toxicological Response Combining Circular Fingerprints with Random Forest and Support Vector Machine
نویسندگان
چکیده
Citation: Koutsoukas A, St. Amand J, Mishra M and Huan J (2016) Predictive Toxicology: Modeling Chemical Induced Toxicological Response Combining Circular Fingerprints with Random Forest and Support Vector Machine. Front. Environ. Sci. 4:11. doi: 10.3389/fenvs.2016.00011 Predictive Toxicology: Modeling Chemical Induced Toxicological Response Combining Circular Fingerprints with Random Forest and Support Vector Machine
منابع مشابه
Application of ensemble learning techniques to model the atmospheric concentration of SO2
In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and re...
متن کاملPredicting the cause of kidney stones in patients using random forest, support vector machine and neural network
Background: Today, with the advancement of technology in various fields, the importance of recording data in the field of health is increasing so much that for many diseases around the world, including kidney disease, registration systems have been set up. This is happening in our country and in the future, the number of these systems will increase. The medical data set contains valuable inform...
متن کاملGaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity
In this article, we extend the application of the Gaussian processes technique to classification quantitative structure-activity relationship modeling problems. We explore two approaches, an intrinsic Gaussian processes classification technique and a probit treatment of the Gaussian processes regression method. Here, we describe the basic concepts of the methods and apply these techniques to bu...
متن کاملPrognosis of multiple sclerosis disease using data mining approaches random forest and support vector machine based on genetic algorithm
Background: Multiple sclerosis (MS) is a degenerative inflammatory disease which is most commonly diagnosed by magnetic resonance imaging (MRI). But, since the MRI device uses of a magnetic field, if there are metal objects in the patient's body, it can disrupt the health of the patient, the functioning of the MRI, and distortion in the images. Due to limitations of using MRI device, screening ...
متن کاملPrediction of true critical temperature and pressure of binary hydrocarbon mixtures: A Comparison between the artificial neural networks and the support vector machine
Two main objectives have been considered in this paper: providing a good model to predict the critical temperature and pressure of binary hydrocarbon mixtures, and comparing the efficiency of the artificial neural network algorithms and the support vector regression as two commonly used soft computing methods. In order to have a fair comparison and to achieve the highest efficiency, a comprehen...
متن کامل