FML-kNN: scalable machine learning on Big Data using k-nearest neighbor joins
نویسندگان
چکیده
منابع مشابه
Evaluating Nearest-Neighbor Joins on Big Trajectory Data
Trajectory data are abundant and prevalent in systems that monitor the locations of moving objects. In a vehicle location-based service, the positions of vehicles are continuously monitored through GPS; each vehicle is associated with a trajectory that describes its movement history. In species monitoring, animals are attached with sensors, whose positions can be frequently traced by scientists...
متن کاملBig Data Classification using Fuzzy K-Nearest Neighbor
Because of the massive increase in the size of the data it becomes troublesome to perform effective analysis using the current traditional techniques. Big data put forward a lot of challenges due to its several characteristics like volume, velocity, variety, variability, value and complexity. Today there is not only a necessity for efficient data mining techniques to process large volume of dat...
متن کاملStock Price Prediction Using K-Nearest Neighbor (kNN) Algorithm
Stock prices prediction is interesting and challenging research topic. Developed countries' economies are measured according to their power economy. Currently, stock markets are considered to be an illustrious trading field because in many cases it gives easy profits with low risk rate of return. Stock market with its huge and dynamic information sources is considered as a suitable environment ...
متن کاملScalable Nearest Neighbor Search based on kNN Graph
Nearest neighbor search is known as a challenging issue that has been studied for several decades. Recently, this issue becomes more and more imminent in viewing that the big data problem arises from various fields. In this paper, a scalable solution based on hill-climbing strategy with the support of k-nearest neighbor graph (kNN) is presented. Two major issues have been considered in the pape...
متن کاملEfficient Processing of k Nearest Neighbor Joins using MapReduce
k nearest neighbor join (kNN join), designed to find k nearest neighbors from a dataset S for every object in another dataset R, is a primitive operation widely adopted by many data mining applications. As a combination of the k nearest neighbor query and the join operation, kNN join is an expensive operation. Given the increasing volume of data, it is difficult to perform a kNN join on a centr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Big Data
سال: 2018
ISSN: 2196-1115
DOI: 10.1186/s40537-018-0115-x