generalization ability
Dynamics and Generalization Ability of LVQ Algorithms
... of generalization in these methods is therefore not clear, often dynamical problems such as divergence of the algorithms can be ...A generalization which allows the incorporation of more general metrics, ...
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Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso
... of generalization ability, the ability of a selected model to predict outcomes in new samples from the same ...population. Generalization ability is important for prediction purposes or ...
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Training Set Size for Generalization Ability of Artificial Neural Networks in Forecasting TCP/IP Traffic Trends
... good generalization will ...the generalization ability of ANNs is ...and generalization ability of other ANN models, including Self Organizing Maps (SOM) and Learning Vector ...
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On the Optimal Learning Rate Size for the Generalization Ability of Artificial Neural Networks in Forecasting TCP/IP Traffic Trends
... Their ability to model almost any kind of function regardless of its degree of nonlinearity, positions them as good candidates for predicting self-similar time series such as TCP/IP ...for generalization ...
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A New Pooling Method For Improvement Of Generalization Ability In Deep Convolutional Neural Networks
... the generalization ability of deep CNNs as well as to avoid overfitting problem on the one hand, and due to the crucial role of pooling mechanism in the CNN and the successful of 𝑙 pooling method on the ...
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Finite sample and asymptotic analysis of generalization ability with an application to penalized regression
... In this paper, we study the performance of penalized and unpenalized extremum estimators from the perspective of generalization ability (GA), the ability of a model to predict outcomes in new samples ...
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SECURE ROUTING IN MANET USING ASYMMETRIC GRAPHS
... in generalization ability and its learning accuracy ...the generalization ability of the model: with the rise of C , the data’s fitting degree tends to increase, but the generalization ...
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Title: An Endowed Takagi-Sugeno-type Fuzzy Model for Classification Problems
... system generalization ability is improved by designing the fuzzy classification model with the help of support vector ...high generalization ability and optimal consequent ...
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Runway Incursion Event Forecast Model based on LS-SVR with Multi-kernel
... excellent generalization ability. However, the generalization ability of SVM often relies on whether the selected kernel function is suitable for real ...improve generalization ...
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Static Prediction Games for Adversarial Learning Problems
... The regularization parameters ρ v of the players v ∈ {− 1 ,+ 1 } play a major role in the prediction game. The learner’s regularizer determines the generalization ability of the predicti[r] ...
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Findings of the WMT 2019 Shared Tasks on Quality Estimation
... • To test the generalization ability of QE approaches in a massive multi-system scenario, instead of learning to estimate the quality of just a single MT system • To directly compare QE [r] ...
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Iris Recognition using Convolutional Neural Network Design
... The designed CNN architecture has given promising results for recognition rate with state of art approaches. The recognition rate obtained is summarized in table 3. The scratch CNN design is used to extract the ...
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A Sleep Staging Method Using Multi parameters
... To verify the generalization ability of this method, cross-validation was used to train and test different samples. The sample slp32 has no REM period, it is easy to cause misjudgment, resulting in lower ...
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Proposing Multimodal Integration Model Using LSTM and Autoencoder
... test generalization capability of trained ...high generalization ability, the model can output the visual images from only motion patterns or motion patterns from only visual image ...that ...
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Data-Distortion Guided Self-Distillation for Deep Neural Networks
... Data Distortion. Data distortion can be taken as a tactic to boost the generalization ability of model (Simard et al. 1996) by alleviating data over-fitting, which is a critical influenc- ing factor of deep ...
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Learning Adaptable Patterns for Passage Reranking
... We use tree structures as our base representation since they provide sufficient flexibility in repre- sentation and allow for easier feature extraction than, for example, graph structures. We rely on the Partial Tree ...
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Face Recognition using One shot Learning
... Poor generalization ability of the one-shot classes is mainly caused by the data imbalance problem, which cannot be effectively addressed by multi-nominal logistic regression that is widely used as the ...
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Primi Isolated Words Spectrogram Classification by Support Vector Machine Based on Immune Genetic Algorithm
... and generalization ability of SVM, this paper fully analyzes the performance of kernel functions, and presents Primi isolated words spectrogram classification using support vector machine optimized by ...
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A Power System Transient Stability Assessment Model Based on Stacked Denoising Autoencoder
... With the rapid development, the computing power of computers has increased dramatically. At the same time, a large number of smart meter devices are connected to the grid to provide a large amount of measurement data, so ...
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Foreground-Background Separation by Feed-forward Neural Networks in Old Manuscripts
... the generalization ability of our neural network, we tested it on the testing collection containing 165 images of new old documents that were not presented to the MLP (25 of the first set and 140 of the ...
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