neural-network based decision algorithms
Comparative Study On Effort Estimation Using Different Data Mining Techniques
... and Neural Network ...Artificial Neural Network, Regression Tree, Regression Analysis, Decision Tree, Random Forest, Logistic Regression, Naive Bayes, K- Nearest Neighbor, ...
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Deep Learning for Stock Market Prediction
... groups based on ten years of historical ...learning algorithms utilized for prediction of future values of stock market ...employed Decision Tree, Bagging, Random Forest, Adaptive Boosting ...
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Implementation of Artificial Neural Networks and Decision Tree Algorithms for Heart Disease Diagnosis
... Cluster Based Association Rule mining for heart disease predictions ...artificial neural network algorithms such as Multilayer Perceptron and decision tree classifiers namely J48 and ...
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Wideband spectrum sensing using adaptive neuro fuzzy inference system in cognitive radio networks
... existing algorithms such energy detection, spectrum sensing based on HSMM and fuzzy neural network based spectrum sensing are plotted versus the false-alarm probability for a detection ...
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A Survey On Data Mining Techniques In Customer Churn Analysis For Telecom Industry
... [11]. Neural Networks are motivated by the ...the neural network neuron with learning algorithms is able to learn from training data; this makes them be referred to as Artificial Neural ...
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Applying Supervised Machine Learning Algorithms for Analytics of Sensor Data
... learning algorithms possesses a capability of self learning and improvisation and they are broadly categorized into three categories: Supervised Learning, Unsupervised Learning and Reinforcement Learning ...The ...
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AN OPTIMISED INTELLECTUAL AGENT BASED SECURE DECISION SYSTEM FOR HEALTH CARE
... are based on relevance of the assigned value (weight) of that particular input ...is. Neural Network algorithms use Linear and sigmoid transfer ...functions. Neural Networks are ...
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Swarm-based Algorithms for Neural Network Training
... The ant colony optimization (ACO) algorithm is, in its original state, an algorithm that is used for discrete optimization problems such as the Travelling Salesperson problem. Thus, some design decisions must be made to ...
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IJCSMC, Vol. 6, Issue. 8, August 2017, pg.49 – 54 A COMPARATIVE STUDY OF DIAGNOSING LIVER DISORDER DISEASE USING CLASSIFICATION ALGORITHM
... analyzed algorithms such as C4.5, Naive Bayes, Decision Tree, Support Vector Machine, Back Propagation Neural Network and Classification and Regression Tree ...result based on speed, ...
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... largely based upon crop ...mining algorithms for rainfall ...algorithm, Decision Tree, Neural Network and fuzzy logic are some of the algorithms compared in this ...
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IJCSMC, Vol. 5, Issue. 5, May 2016, pg.483 – 488 A Survey on Classification Techniques in Data Mining for Analyzing Liver Disease Disorder
... analyzed algorithms such as C4.5, Naive Bayes, Decision Tree, Support Vector Machine, Back Propagation Neural Network and Classification and Regression Tree ...result based on speed, ...
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Survey on Vertical Handoff Decision
... each network parameter based on the network-provider’s and the end- users’ ...wireless network for a particular service that can satisfy end-users’ preferences such as low cost, good RSS, ...
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Plant Disease Prediction using Machine Learning Algorithms
... It is for partitioning where each cluster center is represented by the mean value of objects in cluster. The input is data set and number of clusters. The output is set of k clusters. The algorithm randomly selects k ...
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Image Object Classification and Identification using Soft Computing Tools: A Review
... Application of neural network plays a major role in image classification. Probabilistic neural network (PNN) is one widely used neural network. The PNN architecture is as shown ...
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Mining Big Data using Genetic Algorithm
... Genetic Algorithms are a clan of computational prototypes inspired by evolution theory of Darwin. According to Darwin the species which is fittest and can adapt to changing surroundings can survive; the remaining ...
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A SURVEY ON PREDICTION OF CARDIO VASCULAR DISEASESUSING DATA MINING TECHNIQUES
... a Decision Support in Heart Disease Prediction System using Naive Bayesian Classification ...Multilayer Neural Network along with Back propagation Learning Algorithm for training the ...of ...
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1. Heart disease and data mining: collaboration in the making
... Abstract: The healthcare sector assemble enormous quantity of healthcare data which cannot extract to uncover secret information for making effectual decision. Although, these data have a plenty of unrevealed ...
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1. Kernel network parameters optimization using optimized artificial neural network to serve quality of service parameters
... CO-ABC based ANN ...datasets. Based on above data set implementation we found the CO-ABC performing the best for exploration and exploitation issue [7] Base on the above experiment we have identify our ...
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FLEXIBLE SHARING IN DHT BASED P2P NETWORKS USING METADATA OF RESOURCE
... traditional algorithms for ML Nonetheless, the computational load is very heavy and multivariate nonlinear maximization problem is ...of neural network (NN) for obtaining the global optimal solution ...
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Scaly Neural Networks for Speech Recognition Using DTW and Time Alignment Algorithms
... the network [6]. As with the decision about the number of hidden units, the size of network tends to be decided on a trial and error basis and the designers own ...connected network and then ...
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