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funModeling (version 1.9.5)

Exploratory Data Analysis and Data Preparation Tool-Box

Description

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

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Version

Install

install.packages('funModeling')

Monthly Downloads

1,890

Version

1.9.5

License

GPL-2

Maintainer

Pablo Casas

Last Published

April 1st, 2024

Functions in funModeling (1.9.5)

concatenate_n_vars

Concatenate 'N' variables
entropy_2

Computes the entropy between two variables
cross_plot

Cross-plotting input variable vs. target variable
data_golf

Play golf
freq

Frequency table for categorical variables
convert_df_to_categoric

Convert every column in a data frame to character
coord_plot

Coordinate plot
df_status

Get a summary for the given data frame (o vector).
discretize_df

Discretize a data frame
data_integrity

Data integrity
range01

Transform a variable into the [0-1] range
data_integrity_model

Check data integrity model
auto_grouping

Reduce cardinality in categorical variable by automatic grouping
funModeling-package

funModeling: Exploratory data analysis, data preparation and model performance
information_gain

Information gain
metadata_models

Metadata models data integrity
categ_analysis

Profiling analysis of categorical vs. target variable
equal_freq

Equal frequency binning
desc_groups

Profiling categorical variable
desc_groups_rank

Profiling categorical variable (rank)
status

Get a summary for the given data frame (o vector).
get_sample

Sampling training and test data
heart_disease

Heart Disease Data
infor_magic

Computes several information theory metrics between two vectors
gain_lift

Generates lift and cumulative gain performance table and plot
tukey_outlier

Tukey Outlier Threshold
discretize_get_bins

Get the data frame thresholds for discretization
v_compare

Compare two vectors
discretize_rgr

Variable discretization by gain ratio maximization
export_plot

Export plot to jpeg file
hampel_outlier

Hampel Outlier Threshold
var_rank_info

Importance variable ranking based on information theory
gain_ratio

Gain ratio
fibonacci

Fibonacci series
prep_outliers

Outliers Data Preparation
plot_num

Plotting numerical data
profiling_num

Profiling numerical data
plotar

Correlation plots
correlation_table

Get correlation against target variable
data_country

People with flu data
compare_df

Compare two data frames by keys