get_sample: Sampling training and test data

In funModeling: Exploratory Data Analysis and Data Preparation Tool-Box

Sampling training and test data

Description

Split input data into training and test set, retrieving always same sample by setting the seed.

Usage

get_sample(data, percentage_tr_rows = 0.8, seed = 987)

Arguments

data	input data source
percentage_tr_rows	percentage of training rows, range value from 0.1 to 0.99, default value=0.8 (80 percent of training data)
seed	to generate the sample randomly, default value=987

Value

TRUE/FALSE vector same length as 'data' param. TRUE represents that row position is for training data

Examples

# Training and test data. Percentage of training cases default value=80%.
index_sample=get_sample(data=heart_disease, percentage_tr_rows=0.8)
# Generating the samples
data_tr=heart_disease[index_sample,]
data_ts=heart_disease[-index_sample,]

funModeling documentation built on May 29, 2024, 3:24 a.m.