BigDataFr recommends: Correct classification for big/smart/fast data machine learning Subjects: Learning (cs.LG); Information Theory (cs.IT) […] Table (database) / Relational database Classification for big/smart/fast data machine learning is one of the most important tasks of predictive analytics and extracting valuable information from data. It is core applied technique for what now understood under data science […]
Documentation
[arXiv] BigDataFr recommends: Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data
BigDataFr recommends: Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data Subjects: Databases (cs.DB) […] This research explores the potential to analyze bank card payments and ATM cash withdrawals in order to map and quantify how people are impacted by and recover from natural disasters. Our approach defines a disaster-affected community’s economic recovery time […]
[arXiv] BigDataFr recommends : Big Data analytics. Three use cases with R, Python and #Spark #datascientist
BigDataFr recommends: Big Data analytics. Three use cases with R, Python and Spark Subjects: Applications (stat.AP); Learning (cs.LG) […] Management and analysis of big data are systematically associated with a data distributed architecture in the Hadoop and now Spark frameworks. This article offers an introduction for statisticians to these technologies by comparing the performance obtained […]
[arXiv] BigDataFr recommends: The Scalable Langevin Exact Algorithm: Bayesian Inference for Big Data
BigDataFr recommends: The Scalable Langevin Exact Algorithm: Bayesian Inference for Big Data Subjects: Methodology (stat.ME); Computation (stat.CO) […] This paper introduces a class of Monte Carlo algorithms which are based upon simulating a Markov process whose quasi-stationary distribution coincides with the distribution of interest. This differs fundamentally from, say, current Markov chain Monte Carlo in […]
[arXiv] BigDataFr recommends: Clustering Mixed Datasets Using Homogeneity Analysis with Applications to Big Data
BigDataFr recommends: Clustering Mixed Datasets Using Homogeneity Analysis with Applications to Big Data Subjects: Machine Learning (stat.ML) […] Clustering datasets with a mix of continuous and categorical attributes is encountered routinely by data analysts. This work presents a method to clustering such datasets using Homogeneity Analysis. An Optimal Euclidean representation of mixed datasets is obtained […]
[arXiv] BigDataFr recommends: Asynchronous Parallel Algorithms for Nonconvex Big-Data Optimization
BigDataFr recommends: Asynchronous Parallel Algorithms for Nonconvex Big-Data Optimization: Model and Convergence Subjects: Optimization and Control (math.OC); Distributed, Parallel, and Cluster Computing (cs.DC) […] We propose a novel asynchronous parallel algorithmic framework for the minimization of the sum of a smooth nonconvex function and a convex nonsmooth regularizer, subject to both convex and nonconvex constraints. […]
[Datasciencecentral] BigDataFr recommends: A methodology for solving problems with DataScience for Internet of Things – Full – #iot
BigDataFr recommends: A methodology for solving problems with DataScience for Internet of Things – Part 1 and 2 […] This two part blog is based on my forthcoming book: Data Science for Internet of Things. It is also the basis for the course I teach Data Science for Internet of Things Course. I will be […]
[arXiv] BigDataFr recommends: Representation of functions on big data associated with directed graphs
BigDataFr recommends: Representation of functions on big data associated with directed graphs Subjects: Classical Analysis and ODEs (math.CA) […] This paper is an extension of the previous work of Chui, Filbir, and Mhaskar (Appl. Comput. Harm. Anal. 38 (3) 2015:489-509), not only from numeric data to include non-numeric data as in that paper, but also […]
[Datasciencecentral] BigDataFr recommends: Ableism in the Numbers – Social Metrification #datascientist
BigDataFr recommends: Ableism in the Numbers – Social Metrification […] Ableism (able + ism) is apparent in many interactions between people. While driving on a road having a posted limit of 60 KPH, I was traveling slower since I expected a red light to soon appear ahead of me. The driver behind me – at […]
[arXiv] BigDataFr recommends: Measuring Economic Activities of China with Mobile Big Data
BigDataFr recommends: Measuring Economic Activities of China with Mobile Big Data Subjects: Social and Information Networks (cs.SI); Computers and Society (cs.CY) […] Emerging trends in smartphones, online maps, social media, and the resulting geo-located data, provide opportunities to collect traces of people’s socio-economical activities in a much more granular and direct fashion, triggering a revolution […]