ggobi/ggally: GGally 1.3.0
Bibliographic record
Abstract
GGally 1.3.0 ggmatrix.print - massive update! Now prints with a ggplot2 facet'ed structure Column titles are now placed in the strip of a plot matrix If there are 16 plots or more, a progress bar is displayed automatically (if interactive). Please look at the documentation for ggmatrix_gtable more details. ggmatrix legend A legend may be added with the legend parameter in ggduo, ggpairs, and ggmatrix May specify a (length two) numeric plot coordinate May specify a (length one) numeric plot position May specify a legend object retrieved from grab_legend ggnostic - New function! Produces a ggmatrix of diagnostic plots from a model object Uses broom to retrieve model information Each column of the plot matrix is a predictor variable. The rows can display the response variables, fitted points, residuals, standardized residuals, leave one out model sigma values, diagonals of the hat matrix, and cook's distance for each point. ggfacet - New function! Produces single ggplot2 object interface is very similar to ggduo and ggpairs fn_switch - New function! Provide many functions in a list but only call one function at run time according to a mapping value Useful for ggnostic for different behavior depending on the y variable Allows for a 'default' value for the default switch case ggmatrix - allow custom labellers for facet labels Added labeller parameter which is supplied to ggplot2::facet_grid() Allows for labels with plotmath expressions ggmatrix and ggplot2::last_plot() If a ggmatrix object is printed, ggplot2::last_plot() will return the plot matrix ggmatrix and ggplot2 labels ggplot2::labs +'ed to a ggmatrix object ggplot2::xlab and ggplot2::ylab may be +'ed to a ggmatrix object ggplot2::ggtitle +'ed to a ggmatrix object (anything that returns a class of "labels" may be added to a ggmatrix object) ggmatrix and ggplot2::ggsave() ggsave now works with ggmatrix objects ggpairs and ggduo check for cardinality (#197) Before creating a ggmatrix object, a check is made for character/factor columns If there are more than 15 (default) unique combinations, an error is thrown. Setting cardinality_threshold parameter to a higher value can fix the problem (knowing single cell plots may take more time to produce) Setting cardinality_threshold parameter to NULL can stop the check ggmatrix plot proportions ggmatrix can set the plot proportions with the parameters xProportions and yProportions These will change the relative size of the plot panels produced. ggally_cor colour aesthetic color must be a non-numeric value ggsurv added boolean to allow for legend to not be sorted fixed bug where censored points with custom color didn't match properly (#185) Vignettes vignettes are now displayed using packagedocs. More info at http://hafen.github.io/packagedocs/ ggally_box_no_facet and ggally_dot_no_facet New methods added as defaults to pair with new ggmatrix print method
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.516 | 0.522 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".