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  • neuron
  • CONCLUSION We have presented in this paper a new measure allowing explicit neuron selection in connectionnist feed-forward models using scalar or euclidean arti cial neurons. (psu.edu)
  • This method based on a measure giving the contribution that a neuron have an another have been applied to multi-layer perceptron and radial basis function networks. (psu.edu)
  • 5 6.1.3 Sensory feature vectors Sensory feature vectors We give each model neuron an individual number and write the value of this neuron into a large column at a position corresponding to this number of node Fig 6.2 Generation of a sensory feature vector. (docplayer.net)
  • Each field of the model retina, which corresponds to the receptive field of a model neuron, is sequentially numbered. (docplayer.net)
  • data
  • The three data mining models had higher accuracy than the LR model. (springer.com)
  • Gain curves of the three data mining models were convexes more closer to ideal curves by contrast with that of the LR model. (springer.com)
  • AUC of the three data mining models were larger than that of the LR model as well. (springer.com)
  • The three data mining models predicted the risk of EGC more effectively in comparison with the LR model. (springer.com)
  • The three data mining models have optimal predictive behaviors over the LR model, therefore can effectively evaluate the risk of EGC and assist clinicians in improving the diagnosis and screening of EGC. (springer.com)
  • Experimental work has been performed on data set obtained from UCI repository site and is partitioned into three different partitions to find out best suitable partition to be applied for various model. (docplayer.net)
  • An ensemble model of Partical Swarm Optimization (PSO) and Support Vector Machine (SVM) was proposed by author s,similarly other author have integrated other techniques to form hybrid or ensemble model and tested the model on various spam related data set available publicly in repository data sites. (docplayer.net)
  • 8 Fisher's linear discriminant Linear classification model is like 1-D projection of data: y = wtx. (docplayer.net)
  • those data points for which this is not true will be misclassified The perceptron criterion tries to minimise the 'magnitude' of misclassification, i.e., it tries to minimise -wtφ(xi)ti for all misclassified points (the set of which is denoted by M): EP(w) = - i M wtφ(xi)ti Why not just count the number of misclassified points? (docplayer.net)
  • Predictive analytics encompasses a range of statistical techniques from predictive modeling , machine learning , and data mining that analyzes current and historical facts to future predictions. (bigopendata.eu)
  • Scoring models process a customer's credit history , loan application , customer data, etc., in order to rank-order by their likelihood of making future credit payments on time. (bigopendata.eu)
  • These categories are in many areas, such as marketing, where they seek out subtle data patterns to answer questions about customer performance, or fraud detection models. (bigopendata.eu)
  • A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task. (appliedaicourse.com)
  • Once the model is built, new classifications can be calculated with new data. (xed.ch)
  • Classification is the processing of finding a set of models (or functions) which describe and distinguish data classes or concepts . (docplayer.net)
  • The objective of classification is the method to build a model of the classifying attribute based upon the other attributes which are not from the training data set . (docplayer.net)
  • As the program does not know anything except our training data, we till try to come up with a correct bias that represents the real model correctly, and we must also make sure that all training examples are correct. (omidrouhani.com)
  • simple
  • 4 6.1.2 Scanning with a simple model retina Recognizing the letter A A simplified digitizing model retina of only 10 x 10 = 100 photoreceptors A crude approximation of a human eye Simply intended to illustrate a general scheme 6.1. (docplayer.net)
  • linear
  • Using these values, the stiffness of the various layers is back calculated using a back analysis program based on multilayer linear elastic theory. (docplayer.net)
  • 10 The Perceptron Φ1(x) w1 f(wtφ(x)) Φ2(x) w2 Φ3(x) w3 f() Activation function Φ4(x) w4 A non-linear transformation in the form of a step function is applied to the weighted sum of the input features. (docplayer.net)
  • prove
  • To safeguard this, a protocol has been developed which requires the contractor to prove that the thickness and stiffness of the pavement layers are according to the design he proposed. (docplayer.net)
  • means
  • Sign + means that the model supports the property, - that it does not. (psu.edu)
  • An important part in that protocol is deflection testing by means of FWD testing and coring to determine the thickness of the layers. (docplayer.net)
  • Gain
  • A final ensemble model is measured in terms of accuracy, precision, recall, F-measure and Gain Chart. (docplayer.net)
  • feature
  • The anomaly detection can be implemented using different techniques such as statistical model, computer immunological approach and machine learning Feature Selection Feature selection is the most crucial step in constructing intrusion detection system . (docplayer.net)
  • machine
  • Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. (oreilly.com)
  • error
  • A suitable ensemble model is chosen based on various error measures calculated after training and testing the models. (docplayer.net)
  • The developed ensemble models are compared with individual models in terms of various error measures like accuracy, precision, recall and F-measure. (docplayer.net)
  • Tree
  • A proposed model is based on this technique for spam e- mail classification, and achieved 94.6% accuracy which is higher than other individual decision tree based techniques like C4.5 .The same techniques is also applied by many other authors. (docplayer.net)
  • input
  • The ANN and SVM models use falling weight deflectometer (FWD) deflection bowl parameters and the total pavement thickness as input. (docplayer.net)
  • An MLP network consists of an input layer with a set of nodes such as input nodes, one or more hidden layers of processing nodes and an output layer of computation nodes. (docplayer.net)
  • accuracy
  • The model showed to be capable of predicting the cement treated base course modulus with a high degree of accuracy and is a quick and powerful tool for scanning the stiffness of cement bound base courses. (docplayer.net)
  • process
  • These are: In , an investigation the impact of applying more sophistication to lower layers in the filtering process, namely extracting information from is presented. (docplayer.net)
  • performance
  • A question often asked is whether or not the pavement really will have the performance as predicted by the contractor or, in other words, do the pavement layers really have the stiffness and thickness as assumed by the contractor in his design analyses. (docplayer.net)
  • Models are managed to monitor the performance of the model. (bigopendata.eu)