Changes:
stepMIV function -
coding.start.model which allows user to have different
coding types for starting and final model. Additionally, the same
function is improved adding the check for its output value -
if (nrow(steps) > 0) {steps <- cbind.data.frame(target = target, steps)}
and correction for miv table for missing/infinite values is
introduced. cat.bin function is performed. If
merging of special case bins is selected (argument
sc.merge), then summary table output reports the bin with
which it is merged. psi and
create.partitions.Changes:
rf.clustering - increased number of maximum clusters
from 30 to 100 for manual selection. For x2y metric,
minsplit and minbucket added in order to speed
up the algorithm. segment.vld - correction for possible 0 and 1 observed
default rate in the prop.test. replace.woe - extended list of elements for WoE check
(c(NA, NaN, Inf, -Inf)).stepMIV function -
offset.vals. The same function, now returns the model
development database also for coding = "dummy".evrs and
interaction.transformer.Changes:
stepFWD and
stepRPC.Changes:
staged.blocks, embeded.blocks and
ensemble.blocks.create.partitions function - risk factors
with more than 10 modalities.Changes:
psi** value added to the output of psi
function (for comparison with cv.zscore`` andcv.chisq```
critical value)cat.bin output consistency for
sc.merge optionsegmentargument in
homogeneity function (has to be of length one)segment.vld parameterized with the new
argument min.leafstepFWD (now AIC value can be possibly considered in the
selection process)interaction.transformer function -
identification of upper bound for partitioningsc in the functions of univariate analysis
extended for -Inf valuenum.slice, cat.slice
and encode.woenzv - near-zero variancesmote - Synthetic Minority Oversampling Techniqueconstrained.logit - constrained logistic
regressionrf.interaction.transformer - extract interactions from
random foresthhi - Herfindahl-Hirschman Indexnormal.test - Multi-period predictive power testconfusion.matrix and cutoff.palette -
confusion matrix analysisush.test and ush.bin - U-shape testing and
binning procedureskfold.idx - indices for K-fold validationfairness.vld - model fairness validationdecision.tree - custom decision tree algorithm and its
predict methodChanges:
print from within the functions (stepMIV,
stepFWD, stepRPC, staged.blocks,
embedded.blocks, ensemble.blocks) replaced
with messsagestepMIV, boots.vld,
segment.vld, scaled.score,
kfold.vld, fairness.vld, evrs,
staged.blocks) to keep the execution time under 10s during
check_win_release()Changes:
imp.outliers function did not replace identified
outliers properly. Small adjustment made
(db[, rf.l] <- rf.imp have been added).nzv - label of the second most frequent values was
wrongly assigned. (cc.lbl.2 = x.cc.lb1 replaced by
cc.lbl.2 = x.cc.lb2)rf.clustering - updated link for x2y metriccc.dummy) in stepwise
regressionsstepFWDr - stepwise regression for mixed risk factor
typesstepRPCr - stepwise regression based on risk profile
concept and mixed risk factor typesstaged.blocks,
embedded.blocks, ensemble.blocks - “stepFWDr”
& “stepRPCr”staged.blocks,
embedded.blocks, ensemble.blocks,
rf.clustering, hhi, evrs) to
decrease the execution time during check_win_release()stepFWD and stepRPC - additional check for
dummy coding and check.start.model
introducedrs.calibration output exteneded. Now, besides
calibrated values it returns also parametersChanges:
cat.bin function adjusted in part after dealing with
special cases.psi - typo in helper function num.bt
corrected (instead of incluse.lowest = TRUE, now
include.lower = TRUE), This change should not affect
previous usage of the psi function because argument
breaks is a single number which already ensures inclusion
of extreme values (for details see ?cut)tbl.correction (tbl_correction),
summary.tbl (summary_tbl),
log.likelihood(log_likelihood),
best.split.num(best_split_num),
best.split(best_split),
best.split.cat(best_split_cat),
sum.adjacent (sum_adjacent),
c.best.split.num(c_best_split_num),
c.best.split(c_best_split),
c.best.split.cat(c_best_split_cat)Changes:
1. pp.testing - description of the
Hosmer-Lemeshow test results changed 2. power - for the
Hosmer-Lemeshow test removed condition which checks if the observed
portfolio default rate is less than predicted one.