The Experts below are selected from a list of 5095305 Experts worldwide ranked by ideXlab platform
Alex Endert - One of the best experts on this subject based on the ideXlab platform.
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a user based visual analytics workflow for exploratory Model Analysis
arXiv: Human-Computer Interaction, 2018Co-Authors: Dylan Cashman, Shah Rukh Humayoun, Florian Heimerl, Kendall Park, Subhajit Das, John F Thompson, Bahador Saket, Abigail Mosca, John T Stasko, Alex EndertAbstract:Many visual analytics systems allow users to interact with machine learning Models towards the goals of data exploration and insight generation on a given dataset. However, in some situations, insights may be less important than the production of an accurate predictive Model for future use. In that case, users are more interested in generating of diverse and robust predictive Models, verifying their performance on holdout data, and selecting the most suitable Model for their usage scenario. In this paper, we consider the concept of Exploratory Model Analysis (EMA), which is defined as the process of discovering and selecting relevant Models that can be used to make predictions on a data source. We delineate the differences between EMA and the well-known term exploratory data Analysis in terms of the desired outcome of the analytic process: insights into the data or a set of deployable Models. The contributions of this work are a visual analytics system workflow for EMA, a user study, and two use cases validating the effectiveness of the workflow. We found that our system workflow enabled users to generate complex Models, to assess them for various qualities, and to select the most relevant Model for their task.
David Jobber - One of the best experts on this subject based on the ideXlab platform.
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logit Model Analysis for multivariate categorical data
Journal of Marketing Management, 1994Co-Authors: David JobberAbstract:Logit Model Analysis of dichotomous dependent and categorical independent variables has great potential in marketing research, supplementing other multivariate techiques such as regression and discriminant Analysis. This paper describes the steps to be taken in its use and by means of a worked example shows how logit Model Analysis can be applied to a marketing research problem.
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incentives and response rates to cross national business surveys a logit Model Analysis
Journal of International Business Studies, 1991Co-Authors: David Jobber, Hafiz Mirza, Kee H WeeAbstract:An experiment was designed to assess the effects of an enclosed incentive (bookmark), a promised incentive (offer of free copy of the survey results), the target country and the nationality of the parent company on response from a sample of American and Japanese-owned foreign subsidiaries. Logit Model Analysis was used to identify main and interaction effects. Both the bookmark and nationality of parent company affected response rates, while the offer of survey results and target country had no effect. No interaction effects were found. The implications for cross-national mail survey research are discussed.
Dylan Cashman - One of the best experts on this subject based on the ideXlab platform.
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a user based visual analytics workflow for exploratory Model Analysis
arXiv: Human-Computer Interaction, 2018Co-Authors: Dylan Cashman, Shah Rukh Humayoun, Florian Heimerl, Kendall Park, Subhajit Das, John F Thompson, Bahador Saket, Abigail Mosca, John T Stasko, Alex EndertAbstract:Many visual analytics systems allow users to interact with machine learning Models towards the goals of data exploration and insight generation on a given dataset. However, in some situations, insights may be less important than the production of an accurate predictive Model for future use. In that case, users are more interested in generating of diverse and robust predictive Models, verifying their performance on holdout data, and selecting the most suitable Model for their usage scenario. In this paper, we consider the concept of Exploratory Model Analysis (EMA), which is defined as the process of discovering and selecting relevant Models that can be used to make predictions on a data source. We delineate the differences between EMA and the well-known term exploratory data Analysis in terms of the desired outcome of the analytic process: insights into the data or a set of deployable Models. The contributions of this work are a visual analytics system workflow for EMA, a user study, and two use cases validating the effectiveness of the workflow. We found that our system workflow enabled users to generate complex Models, to assess them for various qualities, and to select the most relevant Model for their task.
Kee H Wee - One of the best experts on this subject based on the ideXlab platform.
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incentives and response rates to cross national business surveys a logit Model Analysis
Journal of International Business Studies, 1991Co-Authors: David Jobber, Hafiz Mirza, Kee H WeeAbstract:An experiment was designed to assess the effects of an enclosed incentive (bookmark), a promised incentive (offer of free copy of the survey results), the target country and the nationality of the parent company on response from a sample of American and Japanese-owned foreign subsidiaries. Logit Model Analysis was used to identify main and interaction effects. Both the bookmark and nationality of parent company affected response rates, while the offer of survey results and target country had no effect. No interaction effects were found. The implications for cross-national mail survey research are discussed.
Lawrence S Phillips - One of the best experts on this subject based on the ideXlab platform.
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minimal Model Analysis of intravenous glucose tolerance test derived insulin sensitivity in diabetic subjects
The Journal of Clinical Endocrinology and Metabolism, 1990Co-Authors: S Welch, S S P Gebhart, R N Bergman, Lawrence S PhillipsAbstract:Although minimal Model Analysis of frequently sampled iv glucose tolerance tests (FSIGTs) to measure insulin sensitivity is well recognized, application has been limited by the need for endogenous insulin secretion. In the present study we determined whether use of exogenous insulin could permit minimal Model assessment of insulin sensitivity (S1) to be extended to diabetic subjects. Normal volunteers had separate FSIGT assessments supplemented with both tolbutamide and insulin to accelerate glucose disappearance, while diabetics had a FSIGT supplemented only with insulin. There was a strong and highly significant correlation between the two assessments in normal subjects (r = 0.87; P < 0.001), and the rank order of S1 generally was maintained with the two assessments over a 3–fold range of S1; however, insulin-determined S1 was 16% lower (3.4 ± 0.4 vs. 4.1 ± 0.4 × 10–4 min/μU-mL; P < 0.01). Diabetic subjects had markedly lower insulin sensitivity than controls (S1 = 0.61 ± 0.16; P < 0.0001). Across all s...
