large training data set
Training Data Sets Construction from Large Data Set for PCB Character Recognition
... Printed circuits board (PCB) is one of the key concepts in electronics used in different fields of industry. Usually, pattern recognition [1] and computer vision [2] algorithms are used to read and identify characters ...
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A Resource Aware MapReduce Based Parallel SVM for Large Scale Image Classifications
... a set of problems with a fixed size. One approach is to split the training data set into a number of smaller data chunks and employs a number of SVMs to process the individual ...
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Building a Sentiment Analysis System Using Automatically Generated Training Dataset
... a large train- ing set for sentiment analysis ...a training data set to build our exper- imental sentiment analysis by using Naive Bayes algorithm and TF-IDF enhance- ...The ...
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Focused training sets to reduce noise in NER feature models
... a large role in current NER systems, allowing significant opportunities for research into op- timizing these features to cater to different ...generic training data in order to al- low for contextual ...
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JPlogP: an improved logP predictor trained using predicted data
... calculated training set only 28 different atom-types were found, but the resultant model still predicted the Martel benchmark set with a respecta- ble RMSE of ...expanded set and using our ...
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Relevance vector machine for optical diagnosis of cancer
... into training and test sets ...the training as well as the test set ...the data is ...the training data points and give conditions on the learning mechanism that ensures that ...
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Gesture recognition in streaming motion data using offline training with a limited training set
... Finally, the HMM classifier. This classifier has to be applied on sequences of frames or otherwise it will lose its value, so instead of feeding it each frame individually we feed it windows of frames. The window size ...
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A large-scale crop protection bioassay data set
... a large-scale drug discovery database containing informa- tion about bioactive molecules, their interaction with molecular targets and their biological effects 1,2 ...These data are manually extracted from ...
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Active learning methods for classification and regression problems
... for large data applications. Their strategy queries for a set of samples according to a distribution as determined by the current separating hyperplane and an adaptive confidence ...fewer ...
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Time Series Classification by Class-Specific Mahalanobis Distance Measures
... CBF data model (Saito, ...the training data set and a large number of time series in the test set (1000), we find that, over ten tests, the average 1-NN classification error rate ...
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Shallow Parsing with PoS Taggers and Linguistic Features
... test data of the four types of learning ...test data receives a class label ...the training data. Tokens not in the training data are treated as wrongly ...the training ...
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Musculoskeletal injuries in British Army recruits: a prospective study of diagnosis specific incidence and rehabilitation times
... epidemiological data for injuries during initial military training in British Army popula- tions ...lost training days and could lead to a reduction in combat effectiveness ...military ...
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Exploring gendered cycling behaviours within a large-scale behavioural data-set
... A more substantial insight is that women’s journeys appear to be highly spatially structured. Since female members are more likely to make weekend journeys, it is not surprising that west London and Hyde Park, relatively ...
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An Improved Algorithm of Binary Balanced Tree with Super Large scale Data Set
... This paper presents SBT Multi-Line Merging Sort algorithm based on the improved SBT sorting algorithm. N knots are grouped into M groups and it offers Multi-Line Merging Sort algorithm of SBT tree and description of two ...
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Exploring gendered cycling behaviours within a large-scale behavioural data-set
... the working day are less common for this subset of female members. Importantly, when selecting on these inter-peak journeys we see substantial differences between the types of journeys being made. For men, many ...
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A fuzzy neighborhood rough set method for anomaly detection in large scale data
... Outliers are the unusual, unexpected patterns in the observed world. Outliers exist extensively in real world, and they are generated from different sources: a heavily tailed distribution or errors in inputting the ...
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Chinese Sentiment Analysis Using Appraiser- Degree-Negation Combinations and PSO
... We present a ADN-scoring method in the paper, which used appraisers, degree adverbs, negations, and their combinations for the sentiment analysis of Chinese sentence. Furthermore, We utilized PSO algorithm to optimize ...
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Universal Grapheme to Phoneme Prediction Over Latin Alphabets
... Written language is one of the defining technologies of human civilization, and has been independently invented at least three times through the course of history (Daniels and Bright, 1996). In many ways written language ...
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An Updated Privacy Paradigm for the Internet of Things
... their data will be collected, used, and disclosed; 2) Choice- individuals should be given choices about whether and how their data will be used; 3) Data Minimization- organizations should seek to ...
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AUTOMATED CELL NUCLEUS SEGMENTATION AND ACUTE MYELOGENOUS LEUKEMIA DETECTION IN BLOOD MICROSCOPIC IMAGES
... HD: Fractals have been used in medicine and science in the past for various quantitative measurements [1]. The fractal dimension D is a statistical quantity that gives an suggestions of how completely a fractal appears ...
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