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

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

Author
Pablo Casas
Date of publication
2016-11-12 15:47:09
Maintainer
Pablo Casas <pabloc@datascienceheroes.com>
License
GPL-2
Version
1.5
URLs

View on CRAN

Man pages

correlation_table
Get correlation against target variable
cross_plot
Cross-plotting input variable vs. target variable
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

Files in this package

funModeling
funModeling/NAMESPACE
funModeling/NEWS
funModeling/data
funModeling/data/heart_disease.rda
funModeling/R
funModeling/R/numbers.R
funModeling/R/common_lib.R
funModeling/R/data.R
funModeling/R/cross_plot.R
funModeling/R/attach.R
funModeling/R/models_lib.R
funModeling/R/target_profiling.R
funModeling/MD5
funModeling/DESCRIPTION
funModeling/man
funModeling/man/filter_vars.Rd
funModeling/man/freq.Rd
funModeling/man/range01.Rd
funModeling/man/get_sample.Rd
funModeling/man/df_status.Rd
funModeling/man/model_performance.Rd
funModeling/man/correlation_table.Rd
funModeling/man/cross_plot.Rd
funModeling/man/equal_freq.Rd
funModeling/man/plotar.Rd
funModeling/man/gain_lift.Rd
funModeling/man/prep_outliers.Rd
funModeling/man/v_compare.Rd
funModeling/man/heart_disease.Rd