MeanAccuracy: 'MeanAccuracy' Asks for a dataframe, a vector of collumn...

In cleanerR: How to Handle your Missing Data

Description

MeanAccuracy Asks for a dataframe, a vector of collumn indices and the goal collumn the expected value of accuracy of filling missing values if the dataset is representative

Usage

MeanAccuracy(df, VECTORS, goal)

Arguments

df	A dataframe that you intend to fill missing values, warning this dataframe shall contain no missing values so the user must drop the lines it happens
VECTORS	The collumns you wish to use to predict the missing values
goal	The collum with the missing values you wish to fill

Examples

#The Mean accuracy function tells its user the expected accuracy.
#Code with two ## is working code but takes longer than 5 seconds
#Given a set and a goal to predict it supposes the following.
#All missing values are representative of the dataset.
#Lets first Consider the iris dataset
#It has the following parameters
print(names(iris))
#As we can see the 5 collumn is species
#Lets use Sepal.Length to predict Species and see Mean accuracy
print(MeanAccuracy(iris,1,5))
#Now lets use both sepal parameters
##print(MeanAccuracy(iris,1:2,5))
#And when using a Petal parameter as well
##print(MeanAccuracy(iris,1:3,5))
#We can see that iris even in the Mean case scenario species can be defined by these 3
#Now lets take a look at the mtcars dataset
##print(names(mtcars))
#Predicting gear using mpg
##print(MeanAccuracy(mtcars,1,10))
#But if we try to predict mpg using gear
##print(MeanAccuracy(mtcars,10,1))
#So using the Mean accuracy function we can know whats the mean case accuracy
#If the user requires he can also predict more than 1 goal for example
##print(MeanAccuracy(mtcars,c(1,3,5),c(10,11)))
#In this case we want to use mpg,disp,drat to predict a pair gear,carb
#To check the confidence of predicted values the user should use all three accuracy functions

cleanerR documentation built on May 2, 2019, 5:51 a.m.