imputeBasic

Imputes the mean or median for continous variables; highest frequency for categorical variables.

An open-source implementation of latent variable methods and multivariate modeling tools. The focus is on exploratory analyses using dimensionality reduction methods including low dimensional embedding, classical multivariate statistical tools, and tools for enhanced interpretation of machine learning methods (i.e. intelligible models to provide important information for end-users).   Target domains include extension to dedicated applications e.g. for manufacturing process modeling, spectroscopic analyses, and data mining.

Nelson Afanador

mvdalab

Multivariate Data Analysis Laboratory

imputeBasic function

<dl><dt>data</dt>
<dd>a dataset with missing values</dd><dt>Init</dt>
<dd>For continous variables impute either the mean or median</dd></dl>

Arguments

Nelson Lee Afanador (<a href="/link/nelson.afanador%40mvdalab.com?package=mvdalab&version=1.7" data-mini-rdoc="mvdalab::nelson.afanador@mvdalab.com">nelson.afanador@mvdalab.com</a>)

Author

Naive imputation of missing values. — imputeBasic

<dl>

<dt>data</dt>
<dd>a dataset with missing values</dd>

<dt>Init</dt>
<dd>For continous variables impute either the mean or median</dd>

</dl>

Nelson Lee Afanador (<a href='mailto:nelson.afanador@mvdalab.com'>nelson.afanador@mvdalab.com</a>)

imputeBasic: Naive imputation of missing values.

Description

Usage

Value

Arguments

Author

Details

Examples