funModeling: Learn Data Science Through the "Data Science Live Book"
Version 1.6.2

Around 10% of almost any predictive modeling project is spent in predictive modeling, 'funModeling' and the book are intended to cover remaining 90%: data preparation, profiling, selecting best variables 'dataViz', assessing model performance and other functions.

AuthorPablo Casas
Date of publication2017-03-16 23:12:10 UTC
MaintainerPablo Casas <pcasas.biz@gmail.com>
LicenseGPL-2
Version1.6.2
URL livebook.datascienceheroes.com
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("funModeling")

Popular man pages

auto_grouping: Reduce cardinality in categorical variable by automatic...
categ_analysis: Profiling analysis of categorical vs. target variable
cross_plot: Cross-plotting input variable vs. target variable
desc_groups: Profiling categorical variable
equal_freq: Equal frequency binning
model_performance: Get model perfomance metrics (KS, AUC and ROC)
v_compare: Compare two vectors
See all...

All man pages Function index File listing

Man pages

auto_grouping: Reduce cardinality in categorical variable by automatic...
bayesian_plot: Cross-plotting input variable vs. target variable
categ_analysis: Profiling analysis of categorical vs. target variable
coord_plot: Coordinate plot
correlation_table: Get correlation against target variable
cross_plot: Cross-plotting input variable vs. target variable
data_country: People with flu data
desc_groups: Profiling categorical variable
desc_groups_rank: Profiling categorical variable (rank)
df_status: Get a summary for the given data frame.
equal_freq: Equal frequency binning
filter_vars: Filtering variables by string name
freq: Frequency table for categorical variables
gain_lift: Generates lift and cumulative gain performance table and plot
get_sample: Sampling training and test data
heart_disease: Heart Disease Data
model_performance: Get model perfomance metrics (KS, AUC and ROC)
plotar: Correlation plots
prep_outliers: Outliers Data Preparation
range01: Transform a variable into the [0-1] range
v_compare: Compare two vectors

Functions

Files

NAMESPACE
NEWS
data
data/data_country.rda
data/heart_disease.rda
R
R/numbers.R
R/common_lib.R
R/data.R
R/data_preparation.R
R/cross_plot.R
R/attach.R
R/models_lib.R
R/target_profiling.R
R/bayesian_plot.R
MD5
DESCRIPTION
man
man/filter_vars.Rd
man/data_country.Rd
man/freq.Rd
man/auto_grouping.Rd
man/range01.Rd
man/coord_plot.Rd
man/get_sample.Rd
man/df_status.Rd
man/model_performance.Rd
man/correlation_table.Rd
man/desc_groups_rank.Rd
man/desc_groups.Rd
man/cross_plot.Rd
man/equal_freq.Rd
man/categ_analysis.Rd
man/plotar.Rd
man/gain_lift.Rd
man/prep_outliers.Rd
man/v_compare.Rd
man/bayesian_plot.Rd
man/heart_disease.Rd
funModeling documentation built on May 19, 2017, 11:47 a.m.

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