Title :
Research on null-value estimation algorithm based on predicted value
Author_Institution :
Network Center, Nanyang Med. Coll., Nanyang, China
Abstract :
Information system composed of multi-source information is usually incomplete information system, the system contains a variety of types of null values. Incomplete information system of air-missing value estimation problem, first introduced abroad to fill the existing empty value method, and compared and analyzed; Secondly, the detailed model based on the similarity between the null value estimation methods (Expectation maximization, SIM-EM), and analyzed when dealing with sparse data problems; again, a problem of sparse data for improved forecasting methods score - the predicted value based on a null value estimation algorithm (Prediction-EM) and introduce a new feature weight method; Finally, experimental results and performance of this algorithm was validated.
Keywords :
estimation theory; expectation-maximisation algorithm; forecasting theory; SIM-EM; air-missing value estimation problem; empty value method; expectation maximization; feature weight method; forecasting methods score; incomplete information system; multisource information; null value estimation algorithm; null value estimation method; null-value estimation algorithm; predicted value; prediction-EM; sparse data problem; Accuracy; Entropy; Estimation; Information systems; Null value; Prediction algorithms; Vectors; Data fusion; Incomplete information system; Null-value;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-3278-8
DOI :
10.1109/ICSESS.2014.6933564
