Building a Machine-Learning Based Antecedent Classifier
Automatic Machine Learning Forgery Detection Based On SVM Classifier
... b. Edge Description: HOG edge algorithm Differing illuminant estimates in neighboring segments can lead to discontinuities in the illuminant map. Dissimilar illuminant estimates can occur for a number of reasons: ...
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Mycofier: a new machine learning based classifier for fungal ITS sequences
... This classifier includes a novel and curated training data set built with a set of sequences from specialized and curated ...for building the Mycofier classifier make it advantageous over BLAST ...
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A Machine Learning Classifier Based on Statistical Method for Small Number of Samples
... the classifier with ideal generalization ability for small sample size is not easy to ...sample classifier exists widely in the real world, especially in the field of biological ...Therefore, ...
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Mobile Malware Detection using Anomaly Based Machine Learning Classifier Techniques
... using machine- learning classifiers to effectively detect mobile malware by choosing the appropriate networking features for classifier inspections, as well as to find the ideal classifier ...
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A novel semisupervised support vector machine classifier based on active learning and context information
... method based on the labeled samples is adopted to change the detection problem into classification 16.. problem and quickly captures the effective RS information w[r] ...
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A Machine Learning-based Framework for Building Application Failure Prediction Models
... In [6], the authors propose a proactive prediction and control system for large clusters. The proposal relies on logs containing six types of events categorized into classes (e.g. the availability of specific systems, or ...
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Sentiment Analysis for Social Media using SVM Classifier of Machine Learning
... Fig. 3. Pseudo code for PSO In earlier years, PSO has been widely accepted in almost many research and application areas. It has been noted that PSO has shown many good results as compared with other existing techniques. ...
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Development of Automated Classifier of Diabetic Retinopathy using Datasets by Machine Learning
... space, prepared with a taking in calculation from streamlining hypothesis that actualizes a taking in inclination got from measurable learning Theory. It is likewise being utilized for some applications, for ...
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Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony.
... was based on clinician visual ...ML classifier is to achieve similar classification performance as the combination of the first and second filters described above, to identify PVA, while discarding artifact ...
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Signature Verification System Based on Support Vector Machine Classifier
... vector machine (SVM) is proposed. The SVM, a learning method introduced by Vapnik et ...classification based on SVM involves training and testing ...
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Fuzzy-Pattern-Classifier Based Sensor Fusion for Machine Conditioning
... theory based multi-sensor fusion built on Fuzzy- ...presented, based on modified versions of the FPC, which results in a robust and reliable detection of ...various machine parameters and decides, ...
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Machine learning building price prediction with green building determinant
... of machine learning model on GB valuation factors for building price prediction compared to conventional building ...model building price prediction based on green ...
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Improving the Scalability of XCS-Based Learning Classifier Systems
... XCS-based classifier systems. (1) Building blocks of knowledge are ex- tracted from smaller problems of a Boolean domain and reused in learning more complex, large-scale problems in the ...
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ECE544NA Final Project: Robust Machine Learning Hardware via Classifier Ensemble
... Fig. 2. Average Bayes Classifier 2) Bagging: Bootstrap aggregating is a popular method to construct ensembles. The basic idea is to first generate many training sets from original training samples by random ...
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Adaptive Particle Swarm Optimization based Credentialed Extreme Learning Machine Classifier (APSO CELMC) for High Dimensional Datasets
... UCI machine learning repository namely blood, bupa, car, contraceptive, credit, diagnostic, ecoli, Ionosphere, mammography, monks – 1, monks – 2, monks – 3, parkinsons, pima, prognostic, sonar, spect, ...
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Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM
... Marcus Alvarez 1,12 , Elior Rahmani 2,12 , Brandon Jew 3 , Kristina M. Garske 1 , Zong Miao 1,3 , Jihane N. Benhammou 1,5 , Chun Jimmie Ye 4 , Joseph R. Pisegna 1,5 , Kirsi H. Pietiläinen 6,7 , Eran Halperin 1,2,9,10,11 ...
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Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data
... Phenotype Finder Screening datasets often consist of tens of thousands of images, or orders of magnitude more. The amount of data is often so sub- stantial that it exceeds the capabilities of a human expert to observe ...
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Machine Learning-based Individual Assessment of Cortical Atrophy Pattern in Alzheimer's Disease Spectrum: Development of the Classifier and Longitudinal Evaluation
... is based on the assumption that the cortical thickness data could be separated into two categories, such as CN and ...solely based on the cortical thickness data, and the clinical risk factors and ...
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Machine Learning applied to Rule-Based Machine Translation
... SVM classifier to reassign the correct verb form to these verbs and thus increase the number of correct forms in the ...verb based on semantic infor- ...the classifier with ...
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Machine learning for smart building applications: Review and taxonomy
... in building automation systems for a long ...system. Learning is the most appropriate alternative in this case, where the optimal policies are not a priori known but can only be developed using data or ...
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