Fixed a bug in write.coeff when only one explanatory
variable has been selected in linear or logistic regression
radiant.model 1.6.7
Fixed documentation for decision tree sensitivity analysis
Added a warning in case an integer overflow occurs in decision
analysis calculations
Fixed an issue where loading a yaml file for decision analysis could
overwrite an existing tree structure
Fixed issues with Permutation Importance, Prediction, and Partial
Dependence plots with stepwise regression is used. Applies to both
logistic and linear regression
radiant.model 1.6.6
Require Shiny 1.8.1. Adjustments related to icon-buttons were made
to address a breaking change in Shiny 1.8.1
Reverting changes that removed req(input$dataset) in
different places
radiant.model 1.6.3
Fix for change in vip package metric name for r2
radiant.model 1.6.0
Added scaling factor for profit calculations in Model > Evaluate
Classification
Replace dplyr::all_equal with all.equal due deprecation warning
Using “Radiant for R” in UI to differentiate from “Radiant for
Python”
Check if the value of mtry for random forest is less than 0 or
larger than the number of variables in the model
Addressed a package documentation issue due to a change in
roxygen2
radiant.model 1.5.0
Improvements to screenshot feature. Navigation bar is omitted and
the image is adjusted to the length of the UI.
Removed all references to aes_string which is being
deprecated in ggplot
Replaced “size” argument, deprecated in ggplot2, with
“linewidth”
Added functionality to create pdp plots, prediction plots
(pred_plot), and permutation importance plots (varimp) for most
available models. Prediction plots are convenient to quickly check for
possible interactions which would take longer to generate using PDP
Added AUC and Adjusted Pseudo R-squared to model fit metrics for
logistic regression
radiant.model 1.4.10
Fix when parsing commands using strsplit on ‘;’
Use dplyr::near to avoid issues with user-provided
probabilities not summing to 1 due to machine tolerance
radiant.model 1.4.8
gsub(“[-]”, ““, text) is no longer valid in R 4.2.0 and above.
Non-asci symbols will now be escaped using stringi
radiant.model 1.4.6
Added option to create screenshots of settings on a page. Approach
is inspired by the snapper package by @yonicd
Download decision analysis and decision tree plots generated using
mermaid (DiagrammeR) to png format
radiant.model 1.4.4
Fix for change in input format for XGBoost that broke
cross-validation
radiant.model 1.4.3
Fix for breaking change in as.vector for data.frames in the
development version of R
radiant.model 1.4.2
Fixed is_empty function clash with
rlang
Adjustments to work with the latest version of shiny
and bootstrap4
radiant.model 1.4.1
Fixed an issue where variables used in Decision Analysis with a one
letter label caused problems evaluating the tree correctly
Provide easier access to payoffs, probabilities, etc. from a solved
Decisions Analysis tree
radiant.model 1.4.0
Allow jitter in regression plots with scatter
Log transformation of nnet::multinom estimates is no longer
needed
radiant.model 1.3.16
Remove missing values from tidy model output
radiant.model 1.3.15
Allow user to include or exclude variables from the coefficient plot
in linear and logistic regression
Fix for error on R-dev in Model > Collaborative
filtering (“Error in xtfrm.data.frame(x) : cannot xtfrm data
frames”)
radiant.model 1.3.14
Fix for issue introduced by version 0.7.0 of the broom package
related to degrees of freedom in linear regression
Fix for NoLD issue (XGBoost) identified by CRAN on Linux
Fix for NoLD issue (XGBoost) identified by CRAN on Solaris
radiant.model 1.3.12
Fix for Model > Decision analysis. Indent levels could
be affected when the input file contains blank lines
Improvement in calculating PDP for categorical variables in plot.gbt
based on suggestion by @benmarchi
(https://github.com/radiant-rstats/radiant.model/issues/4)
radiant.model 1.3.9
Minor adjustments in anticipation of dplyr 1.0.0
radiant.model 1.3.8
Fix for cv.rforest when the max of mtry exceeds the
number of explanatory variables
Fix to write.coeff when one or more coefficients have a missing
value
Use weighted mean and sd in write.coeff function when needed
Added flexibility in using constants while defining the spec for
other randomly generated variables
radiant.model 1.3.5
Adding OR% change as a columns in output for Model
> Logistic regression and the write.coeff
function
Restrict max number of levels in a “groupable” variable used in
Model > Evaluate classification and Model >
Multinomial logistic regression to no more than 50
Avoid rounding the profit measures in Model > Evaluate
classificiation
radiant.model 1.3.2
Improvements to cv.gbt to allow previously setup evaluation
functions to be used in cross validation for hyper parameter tuning
Random Forest module using the ranger package. Includes
a cv.rforest function for tuning using
cross-validation
Gradient Boosted Trees module using the xgboost
package. Includes a cv.gbt function for tuning using
cross-validation. For convenience, all data.frame-to-matrix-conversion
is handled by radiant
Partial Dependence Plots for all trees-based estimation modules and
for neural networks
onehot function to make converting a data.frame with
categorical variables to a matrix a bit easier
radiant.model 1.3.0
Allow specification of multiple summary functions in Model >
Simulate > Repeat
Documentation updates to link to new video tutorials
Use patchwork for grouping multiple plots together
Allow formula input for logistic and
regress functions
Adjust correlation plot for NB to accommodate changes in Basics
> Correlation
Fix for repeated simulation (Model > Simulate >
Repeat) where “Variables to re-simulate” and “Output variables”
were not always updated correctly when the set of available variables
changed
radiant.model 1.2.7
Fix prediction issue when using I(x^2) in a stepwise estimation
process and x is removed
Fix issue finding .as_int and .as_num when use radiant through shiny
server
radiant.model 1.2.5
Option to drop the intercept for Model > Multinomial Logistic
Regression
Provide access to the variables in a dataset during simulation and
repeated simulation.
radiant.model 1.2.2
Various fixes related to stepwise estimation of Multinomial,
Logistic, and Linear regression model (e.g., VIF calculation, models
with only an intercept, perfect multicollinearity, etc.).
radiant.model 1.2.1
Fix to ensure environment is not attached as an attribute to data
frames generated in the Model > Simulate tool
radiant.model 1.2.0
Update action buttons that initiate calculations when one or more
relevant inputs are changed. When, for example, a model should be
re-estimated, a spinning “refresh” icon will be shown
Add option to use a formula for the regress
function
Improved description of standardization process used. Added link to
Gelman
2008
Added an influence plot that shows standardized residuals and
cooks-distance
radiant.model 1.1.10
Fix for nobs in Model > Multinomial logistic
regression.
Fix for write.coeff for use with Model >
Multinomial logistic regression
Fix for decision trees that reference sub-trees. Environment to
evaluate the tree is now explicitly provided. This will now also work
with (sub) trees loaded from .yaml files
Decision analysis now allows basic formulas in all parts of the
tree
Added confusion matrix and misclassification error for Model
> Multinomial Logistic regression (MNL)
Fix for saving multiple residual series for MNL
Added a module for Multinomial Logistic regression (MNL) in the
Model > Estimate menu
Fix for confusion matrix which couldn’t find find the selected
dataset in the web-interface
Documentation fixes and updates
Improved checks for variables that show no variation
Numerous small code changes to support enhanced auto-completion,
tooltips, and annotations in shinyAce 0.4.1
Automatically fix faulty spacing in user input in Model >
Decision Analysis
radiant.model 1.0.0
Keyboard shortcut (Enter) when defining variable in Model >
Simulate
Allow series of type ts and date in models and prediction
Autocompletion for functions in Model > Simulate
Require shinyAce 0.4.0
radiant.model 0.9.9.3
Don’t use simulation variables when their type is not selected
Provide auto-completion for variables and relevant functions in the
Simulate > Functions input
Keyboard shortcuts for add a defined variable (i.e., press enter
after adding the last input value)
radiant.model 0.9.9.2
Fix for variable definition in Model > Simulate where
names of discrete random variables were not properly ‘fixed’
Fix for variable selection in Model > Decision analysis >
Sensitivity
radiant.model 0.9.9.0
Allow any variable in the prediction dataset to be used to customize
a prediction when using Predict > Data & Command
Fix for write.coeff when interactions, quadratic,
and/or cubic terms are included in a linear or logistic regression
Rescale predictions in cv.nn so RMSE and MAE are in the
original scale even if the data were standardized for estimation
Rename scaledf to scale_df for
consistency
Fix for plot sizing and printing of missing values in collaborative
filtering
Fix for cv.nn when weights are used in estimation
Improve documentation for cross-validation of nn and
crtree models (i.e., cv.nn and
cv.crtree)
Fixes for breaking changes in dplyr 0.8.0
Fix to download tables from Model > Evaluate
classificiation
Use an expandable shinyAce input for the formula and
function inputs in Model > Simulate
Fixes for repeated simulation with grid-search
Use test instead of validation
radiant.model 0.9.8.0
Option to add user defined function to simulations. This
dramatically increases the flexibility of the simulation tool
Ensure variable and dataset names are valid for R (i.e., no spaces
or symbols), “fixing” the input as needed
Cross validation functions for decision trees
(cv.crtree) and neural networks(cv.nn) that
can use various performance metrics for during evaluation e.g.,
auc or profit
Option to add square and cube terms in Model > Linear
regression and Model > Logistic regression.
Option to pass additional arguments to shiny::runApp
when starting radiant such as the port to use. For example,
radiant.model::radiant.model(“https://github.com/radiant-rstats/docs/raw/gh-pages/examples/demo-dvd-rnd.state.rda”,
port = 8080)
Avoid empty string showing up in auto-generated code for model
prediction (i.e., pred_data or pred_cmd)
Fix for VIF based on car for regress and
logistic
Load a state file on startup by providing a (relative) file path or
a url. For example,
radiant.model::radiant.model(“https://github.com/radiant-rstats/docs/raw/gh-pages/examples/demo-dvd-rnd.state.rda”)
Don’t live-update the active tree input to make it easier to save
edits to a new tree without adding edits to the existing tree (Model
> Decision analysis)
Fix for NA error when last line of a decision analysis input is a
node without a payoff or probability
Load input (CMD + O) and Save input (CMD + S) keyboard shortcuts for
decision analysis
radiant.model 0.9.7.0
Major changes
Using shinyFiles
to provide convenient access to data located on a server
Minor changes
Fix for simulations that use a data set as part of the analysis
Replace non-ASCII characters in example datasets
Remove rstudioapi as a direct import
Revert from svg to png for plots in
_Report > Rmd_ and _Report > R_.svg` scatter plots
with many point get to big for practical use on servers that have to
transfer images to a local browser
Removed dependency on methods package
radiant.model 0.9.5.0
Major changes
Various changes to the code to accommodate the use of
shiny::makeReactiveBinding. The advantage is that the code
generated for Report > Rmd and Report > R will
no longer have to use r_data to store and access data. This
means that code generated and used in the Radiant browser interface will
be directly usable without the browser interface as well.
Improved documentation and examples
radiant.model 0.9.2.3
Bug fixes
Fix for https://github.com/radiant-rstats/radiant/issues/53
radiant.model 0.9.2.2
Major changes
Show the interval used in prediction for Model >
Regression and Model > logistic (e.g., “prediction” or
“confidence” for linear regression)
Auto complete in Model > Decision analysis now provides
hints based on the current tree input and any others defined in the app.
It also provides suggestions for the basic element of the tree (e.g.,
type: decision, type: chance,
payoff, etc.)
Updated user messages for Model > Decision analysis when
input has errors
radiant.model 0.9.2.1
Major changes
Default interval for predictions from a linear regression is now
“confidence” rather than “prediction”
Estimate model button indicates when the output has
been invalidated and the model should be re-estimated
Combined Evaluate classification Summary and Plot into
Evaluate tab
Upload and download data using the Rstudio file browser. Allows
using relative paths to files (e.g., data or images inside an Rstudio
project)
Minor changes
Require shinyAce 0.3.0 in radiant.data and
useSoftTabs for Model > Decision Analysis
radiant.model 0.9.1.0
Major changes
Add Poisson as an option for Model > Simulate
Bug fixes
Fix for #43 where
scatter plot was not shown for a dataset with less than 1,000 rows
Fixed example for logistic regression prediction plot
Fix for case weights when minimum response value is 0
radiant.model 0.9.0.15
Minor changes
Allow character variables in estimation and prediction
Depend on DiagrammeR 1.0.0
radiant.model 0.9.0.13
Major changes
Residual diagnostic plot for Neural Network regression
Improved handling of case weights for logistic regression and neural
networks
Minor changes
Show number of observations used in training and validation in
Model > Evaluate classification
Use Elkan’s formula to adjust probabilities when using
priors in crtree (rpart)
Added options to customize tree generated using crtree
(based on rpart)
Better control of tree plot size in plot.crtree
Cleanup of crtree code
Improved printing of NN weights
Option to change font size in NN plots
Keyboard shortcut: Press return when cursor is in textInput to store
residuals or predictions
Bug fixes
Fix for tree labels when (negative) integers are used
radiant.model 0.9.0.8
Minor changes
Cleanup of lists returned by evalbin and
confusion
Add intercept in coefficient tables that can be downloaded for
linear and logistic regression or using write.coeff
Convert logicals to factors in crtree to avoid labels
< 0.5 and >= 0.5
Improved labeling of decision tree splits in crtree.
The tooltip (aka hover-over) will contain all levels used, but the tree
label may be truncated as needed
Bug fixes
Fix input reset when screen size or zoom level is changed
radiant.model 0.9.0.4
Renamed ann to nn. The ann
function is now deprecated
radiant.model 0.9.0.3
Major changes
Prediction confidence interval provided for logistic regression
based on blog post by [Gavin Simpson]
(https://www.fromthebottomoftheheap.net/2017/05/01/glm-prediction-intervals-i/)
Argument added to logistic to specify if profiling or
the Wald method should be used for confidence intervals. Profiling will
be used by default for datasets with fewer than 5,000 rows
radiant.model 0.9.0.2
Minor changes
Left align tooltip in DiagrammeR plots (i.e., Model >Decision
Analysis and Model > Classification and regression
trees)
Add information about levels in tree splits to tooltips (Model
> Classification and regression trees)
Bug fixes
Fix to ensure DiagrammeR plots are shown in Rmarkdown report
generate in Report > Rmd or Report > R
radiant.model 0.9.0.1
Major changes
Added option to generate normally distributed correlated data in
Model > Simulate
Added option to generate normally distributed simulated data with
exact mean and standard deviation in Model > Simulate
Long lines of code generated for Report > Rmd will be
wrapped to enhance readability
Minor changes
Default names when saving Decision Analysis input and output are now
based on tree name
Allow browser zoom for tree plots in Model > Decision Analysis
and Model > Classification and Regression Trees
Enhanced keyboard shortcuts for estimation and reporting
Applied styler to code
Bug fixes
Grid search specs ignored when Model > Simulate >
Repeat is set to Simulate
The number of repetitions in Model > Simulate was NA when grid
search was used
Fix for large weights that may cause an integer overflow
Minor fix for coefficient plot in plot.logistic
Fixed state setting for decision analysis sensitivity input
Fixed for special characters (e.g., curly quote) in input for Model
> Decision Analysis
Check that costs are not assigned to terminal nodes in Decision
Analysis Trees. Specifying a cost is only useful if it applies to
multiple nodes in a branch. If the cost only applies to a terminal node
adjust the payoff instead
Ensure : are followed by a space in the YAML input to Model >
Decision Analysis
radiant.model 0.8.7.4
Minor change
Upgraded dplyr dependency to 0.7.1
Upgraded tidyr dependency to 0.7
Bug fix
Fix in crs when a tibble is passed
radiant.model 0.8.3.0
Major change
Added option to use robust standard errors in Linear
regression and Logistic regression. The HC1
covariance matrix is used to produce results consistent with Stata
Minor changes
Moved coefficient formatting from summary.regress and
summary.logistic to make result$coeff more easily accessible
Added F-score to Model > Evaluate classification >
Confusion
Bug fixes
Fixed RSME typo
Don’t calculate VIFs when stepwise regression selects only one
explanatory variable
radiant.model 0.8.0.0
Major changes
Added Model > Naive Bayes based on e1071
Added Model > Classification and regression trees based on
rpart
Added Model > Collaborative Filtering and example dataset
(data/cf.rda)
Various enhancements to evaluate (binary) classification models
Added Garson plot and moved all plots to the ANN > Plot tab
Minor changes
Improved plot sizing for Model > Decision Analysis
Show progress indicators if variable acquisition takes some
time
Expanded coefficient csv file for linear and logistic
regression
Show dataset name in output if dataframe passed directly to analysis
function
As an alternative to using the Estimate button to run a model you
can now also use CTRL-enter (CMD-enter on mac)
Use ALT-enter as a keyboard short-cut to generate code and sent to
Report > Rmd or Report > R
Improved documentation on how to customize plots in Report >
Rmd or Report > R
Bug fixes
Multiple tooltips in sequence in Decision Analysis
Decision Analysis plot size in PDF was too small
Replace histogram by distribution in regression plots
Fix bug in regex for overlapping labels in variables section of
Model > Decision Analysis
Fixes for model with only an intercept (e.g., after stepwise
regression)
Update Predict settings when dataset is changed
Fix for predict when using center or standardize with a command to
generate the predictions
Show full confusion matrix even if some elements are missing
Fix for warnings when creating profit and gains charts
Product dropdown for Model > Collaborative filtering did not list
all variables