Regression techniques are one of the most popular statistical techniques used for predictive modeling and data mining tasks. On average, analytics professionals know only 2-3 types of regression which are commo
Regression analysis also allows us to compare the effects of variables measured on different scales, such as the effect of price changes and the number of promotional activities. These benefits help market researchers / data analysts / data scientists to eliminate and evaluate the best set of varia...
Transcriptional heterogeneity among malignant cells of a tumor has been studied in individual cancer types and shown to be organized into cancer cell states; however, it remains unclear to what extent these states span tumor types, constituting general features of cancer. Here, we perform a pan-ca...
majority of these mutations are mutually exclusive, and integrative data analysis reveals mutation-specific distinct driver gene expression programs and biomarkers in UF6,7. Importantly, in addition to the recurrent somatic alterations, population-level studies indicate the presence of yet-to-be-clearly ...
Identifying pathogenic variants from the vast majority of nucleotide variation remains a challenge. We present a method named Multimodal Annotation Generated Pathogenic Impact Evaluator (MAGPIE) that predicts the pathogenicity of multi-type variants. MAG
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A multiple stepwise logistic regression model identified four statistically significant factors associated with lower likelihoods of consistent condom use with male clients: age group, substance abuse, lack of an “employment” arrangement, and having no HIV test within the prior 6 months. In a ...
Data were a nationally representative sample of U.S. children aged 10–17 years (N=1,959), collected in 2013–2014. Latent class analysis was conducted on 22 types of childhood adversity. Regression models examined associations with mental health and substance use. These secondary analyses were ...
The aim of this modeling technique is to maximize the prediction power with minimum number of predictor variables. It is one of the method to handlehigher dimensionalityof data set. Lasso Regression 【惩罚因子为L1范数而非L2范数】 Similar to Ridge Regression, Lasso (Least Absolute Shrinkage and Se...
Single cell technologies are rapidly generating large amounts of data that enables us to understand biological systems at single-cell resolution. However, joint analysis of datasets generated by independent labs remains challenging due to a lack of consi