[PDF] Top 20 A Novel Class Imbalance Learning Method using Neural Networks
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A Novel Class Imbalance Learning Method using Neural Networks
... availability. Class imbalance is a one of the problem arises due to data source which provide unequal class ...one class in a training data set vastly outnumber examples of the other ... See full document
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A novel method for Handwritten Digit Recognition with Neural Networks
... Shape describes a spatial region. Most shapes are a 2-D space. Shape recognition[1] works on the similarity measure so that it can determine that two shapes correspond to each other. The recognition needs to respect the ... See full document
8
Survey on deep learning with class imbalance
... addressing class imbalance with ...cost-sensitive method that incorporates pre-defined misclassification costs into the CE loss function was used by Wang et ...prior class probabili- ties can ... See full document
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A Novel Method for Face Recognition Using Neural Networks with Optical and Infrared Images
... Linear Discriminant Analysis, or simply LDA, is a well- known classification technique that has been used successfully in many statistical pattern recognition problems. The primary purpose of LDA is to separate samples ... See full document
5
Motor Learning Based on the Cooperation of Cerebellum and Basal Ganglia for a Self Balancing Two Wheeled Robot
... A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of ...motor learning method derives from the ... See full document
12
An Approach to Classify Heritage Sites Architecture Using Convolution Neural Networks
... [2]. Learning features from data of interest is considered as a plausible method of remedying the limitations of handcrafted features and at this time, using Convolutional Neural ... See full document
6
Multi objective evolution of artificial neural networks in multi class medical diagnosis problems with class imbalance
... a novel multi-objective opti- misation approach to solving both the problem of finding good structural and parametric choices in an ANN and the problem of training a classifier with a heavily skewed data ... See full document
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Class imbalance ensemble learning based on the margin theory
... each class in a data-set plays an important role in machine ...from class imbalance. Dealing with multi-class tasks with different misclassification costs of classes is harder than dealing ... See full document
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DATA-DRIVEN TECHNIQUES FOR DIAGNOSING BEARING DEFECTS IN INDUCTION MOTORS
... each class sample ...rare class [78, 79]. Various cost-sensitive learning techniques have been developed for CIL including cost-sensitive decision trees (CSDT) [80], cost- sensitive neural ... See full document
109
A Novel Class Imbalance Learning using Ordering Points Clustering
... increase class imbalance in each of these data sets by randomly under sampling the minority class of defaulters, so as to identify to what extent the predictive power of the respective techniques is ... See full document
10
Ensemble based novel class identification for Class Imbalance under sampled Data
... others. Imbalance has a serious impact on the performance of ...classifiers. Learning algorithms that do not consider class imbalance tend to be overwhelmed by the majority class and ... See full document
5
Application of Convolutional Neural Networks to Four-Class Motor Imagery Classification Problem
... a novel feature extraction method oriented to convolutional neural networks (CNN) is discussed in order to solve four-class motor imagery classification ...four- class motor ... See full document
14
Leveraging Smartphone Sensor Data for Human Activity Recognition
... application using accelerometer and gyroscope sensors as well as GPS signals to detect seven ...supervised learning approach for activity ...unsupervised learning method for human activity ... See full document
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Generating Natural Language Descriptions for Semantic Representations of Human Brain Activity
... deep learning methods, which have gained in- terest as an effective approach to automat- ically describe natural language expres- sions for various type of multi-modal in- formation, such as ...deep ... See full document
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A New Method for Intrusion Detection Using Genetic Algorithm and Neural network
... There are two basic reasons for using Nilam Diyodi and Apranga Trapathy in the technique of solidarity events in the network intrusion detection system in 2015. First, the detection of network attacks is usually ... See full document
10
Data Mining using Neural Networks
... solving a problem through simulated annealing will prove incompatible with that of virtual machines or we can say that while working with virtualization of machines it will be quite incompatible with that of the features ... See full document
6
Deep Learning Based Visual Tracking: A Review
... a novel visual tracking algorithm based on a template selection strategy constructed by deep reinforcement learning ...gradient method on numerous training episodes randomly generated from a tracking ... See full document
5
Recognizing Handwritten Alphabets using Neural Networks
... The second step of the recognition system is to process the image file acquired in the first step. This process is crucial to the whole system as it affects the accuracy as well as efficiency of the system. In this ... See full document
5
A Novel Method to Compute Resonant Frequency of Metamaterial Based Patch Antennas Using Neural Networks
... The antenna is found to achieve a good miniaturisation of 43% when compared with the conventional patch antenna. A square shaped CSRR was chosen as they can be easily realised. Since Photolithographic techniques are used ... See full document
7
An agent based method for predicting monthly maximum & minimum quote prices
... artificial neural networks (ANNs), researchers and investors are hoping that the market mysteries can be ...artificial neural networks have been popularly applied to finance problems such as ... See full document
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