Missing Data using Decision Forest and Computational Intelligence

Autor:	Moon, D., Marwala, T.
Rok vydání:	2008
Předmět:	Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	Autoencoder neural network is implemented to estimate the missing data. Genetic algorithm is implemented for network optimization and estimating the missing data. Missing data is treated as Missing At Random mechanism by implementing maximum likelihood algorithm. The network performance is determined by calculating the mean square error of the network prediction. The network is further optimized by implementing Decision Forest. The impact of missing data is then investigated and decision forrests are found to improve the results.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/0812.1615 Zobrazit plný text záznamu View this record from Arxiv