Sensitivity analysis using data pre-2000 only
Pre-cues’ elevation of sensitivity is not only pre-attentive, but largely monocular
... It is noteworthy that the average B0-cue^ same-eye thresh- old is almost identical to the B0-cue^ different-eye threshold. On average, these conditions produced the highest thresholds in Experiment 1. We also conducted ...
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Youtube Data Sensitivity and Analysis using Hadoop Framework
... distributed, data intensive computing. The framework breaks up large data into smaller parallelizable chunks and handles scheduling ▫ Maps each piece to an intermediate value ▫ Reduces intermediate values ...
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Determinants of Sanctions Effectiveness: Sensitivity Analysis Using New Data
... In contrast, some factors are found to be relevant at the threat stage, but are either not related or related in the opposite directions at the imposition stage. Some variables, including Carrots, Democratic Target, ...
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Sensitivity Analysis for Data Mining
... Sensitivity analysis methods estimate the rate of change in the output of a model,which is caused by the changes of the model ...[15]. Sensitivity analysis has been ap- plied in various fields ...
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Opening Black Box Data Mining Models Using Sensitivity Analysis
... commonplace. Data Mining (DM) enables the extraction of knowledge from such databases to the domain user or decision maker ...a data-driven model that learns an unknown underlying function that maps several ...
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Sensitivity analysis using risk measures
... the sensitivity analysis is demon- strated, using the example of a non-linear insurance loss ...The analysis is performed on a Monte-Carlo sample of the ...output only, but no direct ...
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Calibrating Noise to Sensitivity in Private Data Analysis
... The power of the noisy sums primitive has been amply demonstrated in [6] , in which it is shown how to carry out many standard datamining and learning tasks using few noisy sum queries. In this paper we consider ...
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Sensitivity Analysis for Incomplete Data and Causal Inference
... the sensitivity of causal estimands in clinical trials with non- ...(ITT) analysis is a pragmatic approach, but the ITT esti- mand does not measure the causal effect of the actual treatment received and is ...
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Sensitivity Analysis in Multiple Imputation for Missing Data
... A data set that contains the variables Y 1 , Y 2 , ...For data sets that have monotone missing patterns, the variables that contain missing values can be imputed sequentially using covariates ...
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Deeper understanding of non-linear geodetic data inversion using a quantitative sensitivity analysis
... global sensitivity analysis (SA) is applied to the non-linear inversion of gravity changes and displacement data which measured in an active volcanic ...this data is based on the solution of ...
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Using sensitivity analysis and visualization techniques to open black box data mining models
... Area Under the Curve (AUC), which weights the area of each ROC class ac- cording to its prevalence in the data [14]. For regression, the Mean Absolute error (MAE) was used [32]. Table 1 shows the best models for ...
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Adjusting for selection effects in epidemiologic studies: why sensitivity analysis is the only "solution".
... failure using the Acute Kidney Injury Network criteria; duration of renal replacement therapy; serum bilirubin; time to liberation from mechanical ventilation; 28-day, hospital, 3 and 6 month survival; ICU and ...
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Learning the impact of data pre-processing in data analysis
... The nodes connected with short straight edges to the latent-feature nodes, represent the meta-features that define the respective latent-features. In Figure 3.5a, as it can be observed, the latent feature that is most ...
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The VBBO data product consists of pre-trade data only, hence there is no option for standalone posttrade
... 6) Additional Fee payable per connection for clients subscribing to feeds using an internet VPN connection. 7) Börse Berlin AG reserves the right, at Börse Berlin AG’s sole discretion, to limit Connection Fees ...
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Excess sensitivity of consumption using micro data in the UK
... Under predictable or expected financial well being changes, myopia would imply that consumption fluctuates equally in response to both positive and negative financial situation variations. Thus, if households are indeed ...
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Reference Based Sensitivity Analysis for Time-to-Event Data
... of using new methods with real data, assuming cen- soring is at random on both arms for the primary ...reference-based sensitivity analysis, we usually fix one arm to be the “reference” arm, ...
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Sensitivity Analysis in Radiological Risk Assessment using Probability Bounds Analysis
... the analysis for a wide and diverse set in various ...and data censoring, ignorance about the details of the physical mechanisms and processes involved and other imperfection in scientific ...
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Relevant Accessible Sensitivity Analysis for Clinical Trials with Missing Data
... complete data methods to then be ...a sensitivity analysis [9], we do not advocate this approach (or other single imputation ...[39]. Only under very specific and unrealistic assumptions is ...
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Missing Data Methodology: Sensitivity analysis after multiple imputation
... should only come from experts who work/have good knowledge of the colorectal cancer field, however in practice it was difficult to find/contact these experts in the ...from using the ...we only ...
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Analysis of NFIRS Data for Sensitivity to Foreclosure and Other Select Features
... foreclosure data from NFIRS and RealtyTrac for the years 2006 to 2011, several variables not under consideration for the study were ...foreclosure, only 1 or 2 family residential structures were considered, ...
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