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In this version I have: * Fixed some bugs in
time_transfer.
In this version I have: * Fixed some bugs in
split_bins,min_max_norm,digits_num.
* Add new function of sql_hive_text_parse for automatic
production of hive SQL * Add new function of sum_table
includes both univariate and bivariate analysis and ranges from
univariate statistics and frequency distributions, to correlations,
cross-tabulation and characteristic analysis.
In this version I have: * Fixed some bugs in
split_bins,time_transfer,cohort_analysis,xgb_filter,feature_selector.
* Rewrite the functions of
plot_bar,plot_density,plot_line,
plot_box,plot_relative_freq_histogram,love_color.
* Add new functions of plot_colors
In this version I have: * Fixed some bugs in
cohort_analysis,time_transfer,get_ctree_rules.
In this version I have: * Fixed some bugs in
plot_bar,missing_proc,char_to_num.
* Rewrite the logic of time_variable . * New function
plot_line is for generating line plots.
In this version I have: * Fixed some bugs in
data_cleansing,plot_table,check_rules.
In this version I have: * Fixed some bugs in
check_rules, time_transfer.
#creditmodel-1.2.2
In this version I have: * Fixed some bugs in
get_ctree_rules,
ks_plot,cross_table.
#creditmodel-1.2.1
In this version I have: * Enhanced strategy analysis
capabilities. * New function rule_value_replace is for
generating new variables by rules. * Fixed some potential bugs in
ks_plot,
perf_table,training_model,process_nas.
In this version I have: * Enhanced strategy analysis
capabilities. * New function replace_value is for replacing
values of some variables. * Fixed some potential bugs in
check_rules,
get_ctree_rules,rules_filter,%alike%.
In this version I have: * New function
plot_distribution
,plot_relative_freq_histogram,
plot_box,plot_density, plot_bar
are for data visualization. * New function swap_analysis is
for swap out/swap in analysis. * New function rules_filter
is used to filter or select samples by rules * Fixed some potential bugs
in char_to_num,
merge_category,check_rules,get_ctree_rules.
In this version I have: * New function
cross_table is for cross table analysis. * Fixed some
potential bugs in data_cleansing,
low_variance_filter,time_variable,plot_vars.
In this version I have: * New function
entropy_weight for is for calculating Entropy Weight. * New
function term_tfidf for computing tf-idf of documents. *
New function plot_oot_perf for plotting performance of over
time samples in the future. * Fixed some potential bugs in
get_breaks,
lift_plot,perf_table,model_result_plot.
* Add a parameter cut_bin to get_breaks
for cutting breaks equal depth or equal width.
In this version I have:
split_bins,
woe_transfertime_series_proc for time series data
processing.ranking_percent_proc,ranking_percent_dict are
for processing ranking percent variables and generating ranking percent
dictionary.read_dt to
read_data and add and parameter pattern
for matching files.traing_xgb,‘xgb_params’save_dt to
save_data and save_data also supports multiple
data frames.In this version I have:
pred_xgb for using xgboost model to
predict new data.get_psi_plots,
psi_plot to plot PSI of your data..p_to_score for transforming
probability to score.multi_left_jion for left jion a list
of datasets fast.read_data for loading csv or txt
data fast.In this version I have:
xgb_filter,
feature_selector, split_bins,
ks_table_plot, ks_psi_plot,
ks_value.pred_score for predicting new data
using scorecard.lr_params_search,
xgb_params_search for searching the optimal parameters.
“random_search”,“grid_search”,“local_search” are available.partial_dependence_plot,
get_partial_dependence_plots for generating partial
dependence plot.cohort_analysis,
cohort_table, cohort_plot for cohort (vintage)
analysis and visualization.perf_table,
roc_plot, ks_plot, lift_plot,
psi_plot for model validation drawings.In this version I have: * Fixed some potential bugs
in get_names, digits_num
In this version I have:
data_exploration for data
exploration.missing_proc,
outliers_proc ,get_nameslasso_filter, AUC&K-S
is added to select the best lambda. In this way, not only can the set of
variables that makes the AUC or K-S maximized be selected, but also the
multicollinearity (which is difficult to eliminate by AIC in stepwise
regression), can be minimized. That means instead of stepwise
regression, the optimal combination of variables can be selected by
lasso to solve the regression problem.K-S or
AUC values corresponding to different lambda.auc_value ks_value,
which can calculate Kolmogorov-Smirnov (K-S) & AUC of multiple model
results quickly.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.