How to Handle your Missing Data


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Documentation for package ‘cleanerR’ version 0.1.1

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AutoComplete 'AutoComplete' Asks for a dataframe, a vector of collumn indices and the goal collumn and returns the data frame with the values filled
AutoCompleteTable 'AutoCompleteTable' Asks for a data.table, a vector of collumn indices and the goal collumn and returns the data frame with the values filled
BestAccuracy 'BestAccuracy' Asks for a dataframe, a vector of collumn indices and the goal collumn and returns the maximum possible value of accuracy of filling missing values
BestAccuracyTable 'BestAccuracyTable' Asks for a data.table, a vector of collumn indices and the goal collumn and returns the maximum possible value of accuracy of filling missing values
BestVector 'BestVector' Asks for a dataframe and some parameters and returns the best combination of collums to predict the missing value
BestVectorTable 'BestVectorTable' Asks for a data.table and some parameters and returns the best combination of collums to predict the missing value
Candidates 'Candidates' Asks for a dataframe and some parameters and returns how close the collums chosen can predict the goal collum Should be used mostly with generate_candidates or preferably BestVector in case you only want the best combination possible for prediction
CandidatesTable 'CandidatesTable' candidates implementation that asks for a data.table object
CompleteDataset 'CompleteDataset' Asks for a dataframe, a vector of collumn indices and the goal collumn and returns the data frame with the values filled
CompleteDatasetTable 'CompleteDatasetTable' Asks for a data.table, a vector of collumn indices and the goal collumn and returns the data frame with the values filled
GenerateCandidates 'GenerateCandidates' Asks for a dataframe and some parameters and returns all possible combinations of collums for prediction that satisfy a given error in input in a list the first element of the list are the combinations while the second is its measure of error,to get the best parameters call BestVector
GenerateCandidatesTable 'GenerateCandidatesTable' Asks for a data.table and some parameters and returns all possible combinations of collums for prediction that satisfy a given error in input in a list the first element of the list are the combinations while the second is its measure of error,to get the best parameters call BestVector
MeanAccuracy '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
MeanAccuracyTable 'MeanAccuracyTable' Asks for a data.table, a vector of collumn indices and the goal collumn the expected value of accuracy of filling missing values if the dataset is representative
NA_VALUES 'NA_VALUES' Asks for a dataframe and returns a table of how many missing values are in each collum
WorstAccuracy 'WorstAccuracy' Asks for a dataframe, a vector of collumn indices and the goal collumn and returns the minimum possible value of accuracy of filling missing values
WorstAccuracyTable 'WorstAccuracyTable' Asks for a data.table, a vector of collumn indices and the goal collumn and returns the minimum possible value of accuracy of filling missing values