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3040130410 of 35883 results
62681.
See Frank Harrell (2001), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/Rrms.
Description
(no translation yet)
Located in Package: r-cran-rms
62682.
GNU R package providing a DBI-compliant interface to MySQL
Summary
(no translation yet)
Located in Package: r-cran-rmysql
62683.
The package implements access to MySQL databases via the DBI interface of R.
Description
(no translation yet)
Located in Package: r-cran-rmysql
62684.
GNU R package providing basic robust statistics
Summary
(no translation yet)
Located in Package: r-cran-robustbase
62685.
This package provides 'essential' robust statistics. The goal of the package is to provide tools allowing to analyze data with robust methods. This includes regression methodology including model selections and multivariate statistics where the authors strive to cover the book "Robust Statistics, Theory and Methods" by Maronna, Martin and Yohai; Wiley 2006.
Description
(no translation yet)
Located in Package: r-cran-robustbase
62686.
GNU R package to prepare and display ROC curves
Summary
(no translation yet)
Located in Package: r-cran-rocr
62687.
ROC graphs, sensitivity/specificity curves, lift charts, and precision/recall plots are popular examples of trade-off visualizations for specific pairs of performance measures. ROCR is a flexible tool for creating cutoff-parametrized 2D performance curves by freely combining two from over 25 performance measures (new performance measures can be added using a standard interface). Curves from different cross-validation or bootstrapping runs can be averaged by different methods, and standard deviations, standard errors or box plots can be used to visualize the variability across the runs. The parametrization can be visualized by printing cutoff values at the corresponding curve positions, or by coloring the curve according to cutoff. All components of a performance plot can be quickly adjusted using a flexible parameter dispatching mechanism. Despite its flexibility, ROCR is easy to use, with only three commands and reasonable default values for all optional parameters.
Description
(no translation yet)
Located in Package: r-cran-rocr
62688.
ROCR features: ROC curves, precision/recall plots, lift charts, cost curves, custom curves by freely selecting one performance measure for the x axis and one for the y axis, handling of data from cross-validation or bootstrapping, curve averaging (vertically, horizontally, or by threshold), standard error bars, box plots, curves that are color-coded by cutoff, printing threshold values on the curve, tight integration with Rs plotting facilities (making it easy to adjust plots or to combine multiple plots), fully customizable, easy to use (only 3 commands).
Description
(no translation yet)
Located in Package: r-cran-rocr
62689.
Performance measures that ROCR knows: Accuracy, error rate, true positive rate, false positive rate, true negative rate, false negative rate, sensitivity, specificity, recall, positive predictive value, negative predictive value, precision, fallout, miss, phi correlation coefficient, Matthews correlation coefficient, mutual information, chi square statistic, odds ratio, lift value, precision/recall F measure, ROC convex hull, area under the ROC curve, precision/recall break-even point, calibration error, mean cross-entropy, root mean squared error, SAR measure, expected cost, explicit cost.
Description
(no translation yet)
Located in Package: r-cran-rocr
62690.
GNU R package for ODBC database access
Summary
(no translation yet)
Located in Package: r-cran-rodbc
3040130410 of 35883 results

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