mvp()
Here are how to use mvp() functions.
A.mvp()
Description:
Create indicator variables for the MVP analysis and automatically perform the subsequent handling according to a sequence of indicator variables for missing values.
Syntax:
|
A.mvp(T) |
During modeling, create indicator variables for MVP analysis and automatically perform the subsequent handling according to sequence A of multiple missing value indicator variables, and return a binary sequence consisting of two bits – the first bit represents a table sequence made up of MVP columns and the second one is sequence Rec of creation and handling records. |
|
A.mvp@r(Rec) |
During scoring, create a table sequence consisting of MVP columns according to sequence A of multiple missing value indicator variables and sequence Rec of creation and handling records. |
Note:
The external library function (See External Library Guide) creates indicator variables for the MVP analysis and automatically perform the subsequent handling according to a sequence of indicator variables for missing values.
Parameter:
|
A |
A sequencev |
|
T |
A sequence of target variable valuesv |
|
Rec |
A sequence of creation and handling records. |
Option:
|
@bnie |
Each option specifies a target type, and options are mutual-exclusive; automatically judge the type when no option is used; the order of priorities of the options is binary, numeric, integer and enumerated. |
Return value:
Sequence
Example:
|
|
A |
|
|
1 |
=T("D://house_prices_train.csv") |
Import modeling data. |
|
2 |
=T("D://house_prices_test.csv") |
Import scoring data. |
|
3 |
=A1.mi("LotFrontage").field(1) |
Return a sequence of indicator variables for missing values in “LotFrontage” . |
|
4 |
=A1.mi("Alley").field(1) |
Return a sequence of indicator variables for missing values inf “Alley”. |
|
5 |
=A1.(SalePrice) |
A sequence of target variable values. |
|
6 |
=[A3,A4].mvp(A5) |
A6(1): A table sequence containing MVP columns; A6(2):A sequence of creation and handling records Rec. |
|
7 |
=A2.mi("LotFrontage").field(1) |
|
|
8 |
=A2.mi("Alley").field(1) |
|
|
9 |
=[A7,A8].mvp@r(A6(2)) |
Return a table sequence made up of indicator variables of MVP columns for the scoring. |
P.mvp()
Description:
The external library function (See External Library Guide) creates indicator variables for the MVP analysis and automatically perform the subsequent handling according to a table sequence/record sequence of indicator variables for missing values.
Syntax:
|
P.mvp(cns, T) |
During modeling, create indicator variables for MVP analysis and automatically perform the subsequent handling according to multiple missing value indicator variables, and return a binary sequence consisting of two bits – the first bit represents a table sequence made up of MVP columns and the second one is sequence Rec of creation and handling records; when the object is a record sequence and when the sequence of column names in column MI, automatically search for the indicator column for the missing values and perform corresponding computation. |
|
P.mvp@r(cns, Rec) |
During scoring, create a table sequence consisting of indicator variables for MVP columns according to missing value indicator variables and sequence Rec of creation and handling records. |
Parameter:
|
P |
A table sequence/record sequence. |
|
T |
A sequence of target variable values. |
|
cns |
A sequence of names of columns ( or column numbers starting from 1) of a record sequence. |
|
Rec |
A sequence of creation and handling records. |
Option:
|
@bnie |
Each option specifies a target type, and options are mutual-exclusive; automatically judge the type when no option is used; the order of priorities of the options is binary, numeric, integer and enumerated. |
Return value:
Sequence
Example:
|
|
A |
|
|
1 |
=T("D://house_prices_train.csv") |
Import modeling data. |
|
2 |
=T("D://house_prices_test.csv") |
Import scoring data. |
|
3 |
=A1.mi("LotFrontage") |
Return a sequence of indicator variables for missing values in “LotFrontage”. |
|
4 |
=A1.mi("Alley") |
Return a sequence of indicator variables for missing values inf “Alley”. |
|
5 |
=A1.derive(A3(#).field(1):MI_LotFrontage,A4(#).field(1):MI_Alley) |
Add MI indicator variable to the data. |
|
6 |
=A5.mvp(["MI_LotFrontage","MI_Alley"],A1.(SalePrice)) |
A6(1): A table sequence containing MVP columns; A6(2): A sequence of creation and handling records Rec. |
|
7 |
=A2.mi("LotFrontage") |
|
|
8 |
=A2.mi("Alley") |
|
|
9 |
=A2.derive(A3(#).field(1):MI_LotFrontage,A4(#).field(1):MI_Alley) |
|
|
10 |
=A9.mvp@r(["MI_LotFrontage","MI_Alley"],A6(2)) |
Return a table sequence made up of indicator variables of MVP columns for the scoring. |
