An Improved Weighted Naive Bayesian Classification Algorithm Based on Multivariable Linear Regression Model

Author(s):  
Xingang Wang ◽  
Xiu Sun
2014 ◽  
Vol 519-520 ◽  
pp. 58-61 ◽  
Author(s):  
Jian Xu ◽  
Bin Ma

In the light of the excellent distributed storage and parallel processing feature of hadoop cluster, a new kind of network public opinion classification method based on Naive Bayes algorithm in hadoop environment is studied. The collected public opinion documents are stored locally according to the HDFS architecture, and whose character words are extracted paralleled in Mapreduce process. Thus the naive Bayesian classification algorithm is parallel encapsulated on cloud computing platform. The MapReduce packaged Naive Bayesian classification algorithm performance is verified and the results show that the algorithm execution speed are significantly improved compared to a single server. Its public opinion classification accuracy rate is more than 85%, which can effectively improve the classification performance of network public opinion and classification efficiency.


2014 ◽  
Vol 8 (5-6) ◽  
pp. 419 ◽  
Author(s):  
Alexandre Larouche ◽  
Andreas Becker ◽  
Jonas Schiffmann ◽  
Florian Roghmann ◽  
Giorgio Gandaglia ◽  
...  

Introduction: We compare the complication rates and length of stay (LOS) of laser transurethral resection of the prostate (L-TURP) versus electrocautery transurethral resection of the prostate (E-TURP) in a population-based cohort. L-TURP has shown enhanced intraoperative safety and equivalent efficacy relative to E-TURP in several high volume centres.Methods: Relying on the Florida Datafile as part of the Healthcare Cost and Utilization Project State Inpatient Databases (SID) between 2006 and 2008, we identified 8066 men with benign prostate hyperplasia who underwent L-TURP or E-TURP. Chi-square and Mann-Whitney tests were used to compare baseline characteristics. A multivariable linear regression model was used to analyze the effect of L-TURP versus E-TURP on complication rates and LOS.Results: Overall complication rates did not differ significantly for L-TURP compared to E-TURP in univariable (8.8 vs. 7.4%, p = 0.1) and multivariable analyses (odds ratio [OR]: 1.06, confidence interval [CI]: 0.85-1.32, p = 0.6). Individuals undergoing E-TURP were less likely to experience a LOS in excess of 1 day (46.2 vs. 59.7%, p < 0.001). A lower risk to experience a LOS in excess of 1 day was confirmed for patients undergoing L-TURP after a multivariable linear regression model (OR: 0.37, CI: 0.23-0.58, p < 0.001), but not for a LOS in excess of 2 days (OR: 0.96, CI: 0.83-1.10, p = 0.2).Conclusions: Patient characteristics and perioperative safety were similar for L-TURP and E-TURP patients. However, LOS patterns demonstrated a modest benefit for L-TURP compared to E-TURP patients.


Sign in / Sign up

Export Citation Format

Share Document