Regardless of the techniques employed for analysis, they are all susceptible to problems inherent in large data sets. This research investigates the impact of large numbers of observations on traditional linear and logistic regression analysis. The use of simulated data sets with known relationships ...
Regression Analysis for Interval-Valued Data 来自 Semantic Scholar 喜欢 0 阅读量: 473 作者:L Billard,E Diday 摘要: When observations in large data sets are aggregated into smaller more manageable data sizes, the resulting classifications of observations invariably involve symbolic data. In this ...
Incomplete covariate data arise in many data sets. When the missing covariates are categorical, a useful technique for obtaining parameter estimates is the... Lipsitz,S. - 《Biometrika》 被引量: 227发表: 1996年 Regression analysis of incomplete medical cost data The accumulation of medical cost ...
Identification of genes required for cellulose synthesis by regression analysis of public microarray data sets Coexpression patterns of gene expression across many microarray data sets may reveal networks of genes involved in linked processes. To identify factors in... S Persson,H Wei,J Milne,... ...
For an example showing how to process this data for deep learning, see Train Variational Autoencoder (VAE) to Generate Images. To restore the path, use the path function. path(oldpath); Image classification Omniglot The Omniglot data set contains character sets for 50 alphabets, divided into...
Another important connection is in the area of anomaly detection, where regression diagnostics originally intended for data analysis and improving the regression model can be used to detect unusual records. The antecedents of correlation and linear regression date back over a century....
1运筹学的核心在于做决策，建立数学模型（包括：目标函数，决策变量和约束条件），然后进一步采用算法对...
Data mining is the use of machine learning and statistical analysis to uncover patterns and other valuable information from large data sets.
Bank transactions are highly confidential. As a result, there are no real public data sets that can be used to investigate and compare anti-money laundering (AML) methods in banks. This severely limits research on important AML problems such as efficienc
Sanguinetti,Guido - 《IEEE Transactions on Pattern Analysis & Machine Intelligence》 被引量: 69发表: 2008年 Dimensionality reduction for clustered data sets We prove that the maximum likelihood solution of the model is an unsupervised generalisation of linear discriminant analysis. This provides a compl...