[PDF] Top 20 siRNA Efficiency Prediction Using Support Vector Machine
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siRNA Efficiency Prediction Using Support Vector Machine
... Thus siRNA alters the regulatory role of mRNA during gene expression by translational ...effective siRNA with good knockdown effects play an important role in cancer detection and ...siRNAs using one ... See full document
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Software Vulnerability Prediction Using Feature Subset Selection and Support Vector Machine
... The starting point in study is the source code (including comments) of a software application that consists of a number of Java files. Each Java file is tokenized into a vector of terms (text processing ... See full document
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Prediction of Tanzanian Energy Demand using Support Vector Machine for Regression (SVR)
... the prediction of energy demand for Tanzania applying support vector machine for regression ...as prediction tool of future energy ... See full document
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Prediction of Solar Irradiation Using Quantum Support Vector Machine Learning Algorithm
... quantum support vector algorithm was simu- lated using Python programming ...quantum support vector algorithm for solar power ... See full document
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River Water Level Prediction in Satellite Images using Support Vector Machine
... In this training phase the watered region identified images are used to train the SVM in order to identify the watered regions in the river image.. The following details the error minimi[r] ... See full document
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Symptom Recommendation using Collaborative Filtering and Disease Prediction using Support Vector Machine
... where W=weight factor, I=input vector and bias. The hyperplane which divides is defined by f(x)=0. Therefore the first class that falls above the hyperplane has f(x)>0 and another class below the plane is ... See full document
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Prediction of Heart Disease Using Machine Learning
... The SVM is a state-of-the-art maximum margin classification algorithm rooted in statistical learning theory. SVM is method for classification of both linear and non-linear data. It uses a non- linear mapping to transform ... See full document
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Carbon Monoxide Prediction in the Atmosphere of Tehran Using Developed Support Vector Machine
... in support vector regression (SVR) as a well-known modeling approach in atmospheric science based on running SVR model many times to predict the next day CO concentrations in ...CO prediction than ... See full document
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Weather Prediction using Linear Regression & Support Vector Machine vide Big Data
... essentially machine learning strategies, generally neural systems while some drew on probabilistic models, for example, Bayesian ...on machine learning for climate expectation we inspected, two of them ... See full document
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Document Classification Using Support Vector Machine
... the prediction has been depicted as ...tool using the cross validation via grid ...Gamma using an inbuilt module of libSVM tools as shown in table ... See full document
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<p>Reducing Opioid Prescriptions by Identifying Responders on Topical Analgesic Treatment Using an Individualized Medicine and Predictive Analytics Approach</p>
... utilize machine learning in the context of an individualized medicine approach for chronic pain ...a machine learn- ing approach is deployed to predict the outcomes of the therapy given the demographic and ... See full document
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Highly Accurate Emergency Vehicle Management for Multiple Path Using Support Vector Machine Based Predictor
... Abstract: Emergency vehicle management (EVM) plays an important role in different lifesaving field such as medicine, fire and safety, and defense etc. The transportation time of the EV mainly depends upon various ... See full document
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Application of Support Vector Machine in Bus Travel Time Prediction
... filter prediction model for bus arrival ...correlation vector machine prediction algorithm based on Bayesian probability, which can obtain arrival time prediction value and error ...by ... See full document
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Implementation Of An Efficient Hybrid Classification Model For Heart Disease Prediction
... The prediction analysis is applied for predicting future possibilities based on the current ...information. Prediction for future possibilities has been made feasible following three major steps named as ... See full document
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Software defect prediction using enhanced relevance vector machine
... for machine learning, support vector machines (SVMs) produce a model function dependent only on a subset of kernel basis functions associated with some of the training samples, ...of support ... See full document
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An Optimal Churn Prediction Model using Support Vector Machine with Adaboost
... Customer churn is a common measure of lost customers. By minimizing churn, a company can maximize its profits. Companies have recognized that existing customers are most valuable assets. Customer retention is important ... See full document
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Stock Market Prediction Using Support Vector Machine
... the vector w, which defines the separating hyper ...training vector belonging to two separate classes, G={(x i , y i )} Where i=1, 2, 3, 4,……N With a hyper ... See full document
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Spatial Prediction of Landslides using Time Series Analysis and Support Vector Machine
... population using a given set of genetic operators known as crossover and ...landslide prediction, the GA is used to optimally choose the conditioning parameters and thereby improving the ... See full document
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An Approach to Efficient Software Bug Prediction using Regression Analysis and Neural Networks
... [11], Support Vector Machines [12], etc have been ...of machine learning algorithms has increased since ...the prediction of number of faults as output ... See full document
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Classification of power disturbances using multilevel support vector Machine
... disturbances using Wavelet-Multi resolution Decomposition and multi-level Support Vector Machine ...level using the wavelet multi- resolution analysis ...input vector for ... See full document
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