Support Vector machine for Regression (SVR)
Prediction of Tanzanian Energy Demand using Support Vector Machine for Regression (SVR)
... This study discusses the influences of economic, energy and environment indicators in the prediction of energy demand for Tanzania applying support vector machine for regression (SVR). ...
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Weather Prediction using Linear Regression & Support Vector Machine vide Big Data
... Linear regression only shows the 2-dimensional model based on confusion matrix case where the data points are linearly ...following Support Vector Machine ...component vector, where x0 ...
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Sales Forecasting using Linear Regression and Support Vector Machine
... ABSTRACT: This scheme aims to provide an insight in the role intelligent forecasting methods can play in the world of Sales Management. An important assumption throughout this investigation is that data originating from ...
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Seeking gene relationships in gene expression data using support vector machine regression
... Using support vector machine regression (SVMR) and gene ontological information, we proposed an approach to identify gene relationships in expression data provided by Genetic Analysis Workshop ...
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Application of Support Vector Machine Regression for Predicting Critical Responses of Flexible Pavements
... of Support Vector Machine (SVM) regression in order to analysis flexible ...the support vector machine regression was used to predict these two critical ...
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Compression of Images using Hierarchical Correlation of Wavelet Coefficients in Support Vector Machine Regression
... of support vector regression (SVR) to approximate functions using a small number of parameters such as signal samples or support vectors ...the support vectors and their weights using ...
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A confidence predictor for logD using conformal regression and a support-vector machine
... The compounds were encoded by the signature molecu- lar descriptor [17], generated by CPSign [18]. A signature molecular descriptor constitutes a vector of occurrences of all atom signatures in the dataset, where ...
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Knowledge Discovery and Diseases Prediction: A Comparative Study of Machine Learning Techniques
... decision support systems for disease classification through a set of medical ...using machine learning ...techniques. Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Neural ...
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Support Vector Machine and Least Square Support Vector Machine Stock Forecasting Models
... the Support Vector Machine and Least Square Support Vector Machine models in stock ...(GARCH), Support Vector Regression (SVR) and Least Square ...
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A nondestructive method for fish freshness determination with electronic tongue combined with linear and non linear multivariate algorithms
... and support vector machine (SVM) were applied comparatively to classify the samples stored at different ...and support vector regression (SVR) were applied comparatively to ...
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A Survey on Intrusion Detection Systems and Classification Techniques
... Learning Machine (ELM) is a new emergent technology which provides good generalization performance for both classification and regression problems at highly fast learning ...though Support ...
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An Effective Machine Learning Approach For Disease Predictive Modelling In Medical Application
... Logistic Regression. Machine learning technique, ...logistic regression, has been implemented to select the cancer gene data via feature ...the machine learning model were ...six ...
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Using Deep Learning and Machine Learning to Detect Epileptic Seizure with Electroencephalography (EEG) Data
... 6 machine learning algorithms (including naïve bayes, logistic regression, support vector machine, random forest and K-nearest neighbours and gradient boosting decision trees) and 3 ...
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A Comparative study of Data Classification Techniques for Coronary Artery Disease
... as Support Vector Machine (SVM), Logistic Regression, and Decision tree can help in classifying the given patients data can help in the prediction of the heart attack in next ten ...
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Ground Ozone Level Prediction Using Machine Learning
... and machine learning models, where polluted ozone day has class 1 and non-ozone day has class ...different machine learning models are used in the prediction of ground ozone level and their fi- nal accuracy ...
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Analysis of Global Warming Using Machine Learning
... Support vector machines, or SVM, are algorithms that use hyperplanes (a line in more than 3 dimension) to create ...space. Support vector regression (SVR) is an extension of this, ...
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Machine learning and statistical approaches to classification – a case study
... linear regression, decision tree, support vector machine, artificial neural network, K-nearest neighbour (K-NN), naive bayes and many others ...as regression and classification have ...
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Co regularised support vector regression
... The idea for mutual influence of multiple predictors appeared in the paper of Blum and Mitchell [2] on classification with co-training. Wang et al. [14] combined the tech- nique of co-training with SVR with a technique ...
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Impact of Physico Chemical Properties for Soils Type Classification of OAK using different Machine Learning Techniques
... forest. Machine Learning algorithms can be used to forecast and automate soil site classes on different soil sample ...supervised machine learning algorithms to classify Oak forest soil ...classification, ...
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Heart Disease Prediction and Performance Assessment through Attribute Element Diminution using Machine Learning
... UCI Machine Learning Repository for predicting the level of heart ...logistic regression, KNN classifier, Support Vector Machine, Kernel Support Vector Machine, ...
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