Impute Module

Module for data imputation and missing value filtering

Types and nested modules

Type/Module Description

Cleaning

MatrixBaseImputation<'a, 'b>

Type definintion for a vector based imputation The imputed values are based on the given whole dataset

VectorBaseImputation<'a>

Type definintion for a vector based imputation. The imputed values are based only on the given array

Functions and values

Function or value Description

imputeBy impute isMissing data

Full Usage: imputeBy impute isMissing data

Parameters:
Returns: 'a[][]

Imputes rows by matrix-based imputation

impute : MatrixBaseImputation<'a[], 'a>

isMissing : 'a -> bool

data : seq<'b>

Returns: 'a[][]

Example

imputeColWiseBy impute isMissing data

Full Usage: imputeColWiseBy impute isMissing data

Parameters:
Returns: 'a[][]

Imputes column-wise by vector-based imputation

impute : VectorBaseImputation<'a>

isMissing : 'a -> bool

data : seq<'b>

Returns: 'a[][]

Example

imputeRowWiseBy impute isMissing data

Full Usage: imputeRowWiseBy impute isMissing data

Parameters:
Returns: 'a[][]

Imputes row-wise by vector-based imputation

impute : VectorBaseImputation<'a>

isMissing : 'a -> bool

data : seq<'b>

Returns: 'a[][]

Example

kNearestImpute k data arr index

Full Usage: kNearestImpute k data arr index

Parameters:
    k : int -
    data : seq<float[]>
    arr : float[]
    index : int

Returns: float

Imputation by k-nearest neighbour

k : int

data : seq<float[]>
arr : float[]
index : int
Returns: float

Example

normal fdata index

Full Usage: normal fdata index

Parameters:
    fdata : seq<float>
    index : int

Returns: float

Imputation by sampling from a gausian normal distribution based on the input vector

fdata : seq<float>
index : int
Returns: float

rnd rnd fdata index

Full Usage: rnd rnd fdata index

Parameters:
    rnd : Random -
    fdata : seq<'a>
    index : int

Returns: 'a

Imputation by random sampling from the input vector

rnd : Random

fdata : seq<'a>
index : int
Returns: 'a

Example