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 |