Machine Learning Methods
Machine learning methods in chemoinformatics
... Vector Machine Support Vector Machine (SVM) 57 maps the data into a high-dimensional space, using a kernel func- tion that is typically ...ular machine-learning methods in ...
14
Machine learning methods for manufacturing
... introduced machine learning methods and using the domain appropriate dataset was performed in less than 10 seconds, with only the neural network and NARX neural networks which pre- dicted the reduced ...
70
Machine learning methods for recommender systems
... This thesis focuses on the development of new machine learning methods that arise primarily in the area of Recommender Systems. Recommender Systems are prevalent and are widely used in many ...
100
Machine Learning Methods for Computer Security
... and machine learning communities interested in advancing the state-of-the-art in the field of secure learning, discussing open problems, and promoting further collaboration between the two ...of ...
30
Machine Learning Methods for Demand Estimation
... six machine learning methods, all of which differ from standard approaches by combining an element of model selection into the estimation proce- ...flexible methods for approximating arbitrary ...
5
An Assessment of Machine Learning Methods for Robotic Discovery
... all machine learning methods are appropri- ...effective machine learning methods, such as neural networks and support vector ...
8
Machine Learning Methods for Kidney Disease Screening
... ABSTRACT MACHINE LEARNING METHODS FOR KIDNEY DISEASE SCREENING by Rathna Ramesh The number of people diagnosed with advanced stages of kidney disease has been rising every ...
71
Machine Learning Methods in Individual Migration Behavior
... MACHINE LEARNING METHODS IN INDIVIDUAL MIGRATION BEHAVIOR 31 Abstract: Machine learning is described as “a field of computer science that gives a machine the ability to ...fact, ...
10
Machine Learning methods for Quantitative Radiomic Biomarkers
... optimal machine-learning methods for radiomic applications is a crucial step towards stable and clinically relevant radiomic biomarkers, providing a non-invasive way of quantifying and monitoring ...
12
A Survey on Machine Learning Methods in Spam Filtering
... Abstract— Email spam or junk e-mail (unwanted e-mail “usually of a commercial nature sent out in bulk”) is one of the major issue of the today's Internet, that cause financial damage to companies and annoying individual ...
8
Machine Learning Methods with Time Series Dependence
... Machine Learning Methods with Time Series Dependence Abstract We introduce the PrAGMaTiSt: Prediction and Analysis for Generalized Markov Time Series of States, a methodology which enhances ...
231
Machine Learning Methods for Diabetes Prediction
... For evaluation, usually, performance measurement of the model depends on the learning process, techniques, and type of data. Numerous performance measurements that has been used in previous research is Accuracy, ...
7
Machine learning methods for fault classification
... 3 Machine Learning For Classification An algorithm is a set of instructions used to convert input values to an output, based on certain ...algorithm. Machine learning is employed in such ...
72
Machine Learning Methods for Speech Recognition
... [27] Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Good- fellow, Andrew Harp, Geoffrey Irving, ...
75
Machine Learning Methods for Cancer Immunology
... for learning sparse networks from a precision matrix using a lasso-based approach; their method demonstrates remarkable computational efficiency with respect to large datasets ...regularisation methods to ...
144
Machine learning methods for omics data integration
... Abstract High-throughput technologies have produced genome-scale transcriptomic and metabolomic data. Integrating omics datasets can depict a more complete picture of many cellular processes. This work presents a new ...
127
Machine learning methods based on diffusion processes
... Abstract This thesis presents three distinct machine learning algorithms based on the mathe- matical formalism and physical idea of diffusion processes. First, the idea of using heat diffusion on a ...
150
Machine learning methods for multimedia information retrieval
... The method achieved the second highest MAP, MiAP, GMiAP and F- measure scores among 18 participants at the ImageCLEF 2012 Photo Anno- tation challenge. In Section 5.3 we extend the biclustering to label by a richer ...
11
Text classification Based on Machine Learning Methods
... of machine learning technology also accelerates the technology of text ...the methods and models used have been described in ...4 methods are used to do word embedding which are word2vec, ...
48
Machine Learning Methods for Septic Shock Prediction
... Aiman A. Darwiche July 2018 Sepsis is an organ dysfunction life-threatening disease that is caused by a dysregulated body response to infection. Sepsis is difficult to detect at an early stage, and when not detected ...
84