Dataset for holding training data
Constructor | Description |
new(s)
Signature: (s:seq<DV * DV>) -> Dataset
|
Construct a dataset from the given sequence of input-output vector pairs |
new(xi, y)
Signature: (xi:seq<int> * y:DM) -> Dataset
|
Construct a dataset with one-hot input elements and given output matrix |
new(x, yi)
Signature: (x:DM * yi:seq<int>) -> Dataset
|
Construct a dataset with given input matrix |
new(xi, onehotdimsx, y)
Signature: (xi:seq<int> * onehotdimsx:int * y:DM) -> Dataset
|
Construct a dataset with one-hot input elements and given output matrix |
new(x, yi, onehotdimsy)
Signature: (x:DM * yi:seq<int> * onehotdimsy:int) -> Dataset
|
Construct a dataset with given input matrix |
new(xi, yi)
Signature: (xi:seq<int> * yi:seq<int>) -> Dataset
|
Construct a dataset of one-hot input and output elements. |
new(xi, onehotdimsx, yi, onehotdimsy)
Signature: (xi:seq<int> * onehotdimsx:int * yi:seq<int> * onehotdimsy:int) -> Dataset
|
Construct a dataset of one-hot input and output elements. |
new(x, y)
Signature: (x:DM * y:DM) -> Dataset
|
Construct a dataset with given input matrix |
Instance member | Description |
AppendBiasRowX()
Signature: unit -> Dataset
|
Append a row of all ones to the input matrix X |
AppendRowX(v)
Signature: v:DV -> Dataset
|
Append a new row |
AppendRowY(v)
Signature: v:DV -> Dataset
|
Append a new row |
Filter(predicate)
Signature: (predicate:(DV * DV -> bool)) -> Dataset
|
Get a new dataset of the entries for which the |
GetSlice(lower, upper)
Signature: (lower:int option * upper:int option) -> Dataset
|
Get a slice of the dataset between |
[i]
Signature: i:int -> DV * DV
|
Get element |
Length
Signature: int
|
The length of the dataset, i.e., the number of columns in input matrix X and output matrix Y |
Normalize()
Signature: unit -> Dataset
|
Normalize the values in the input matrix X and output matrix Y to be in the range [0,1] |
NormalizeX()
Signature: unit -> Dataset
|
Normalize the values in the input matrix X to be in the range [0,1] |
NormalizeY()
Signature: unit -> Dataset
|
Normalize the values in the output matrix Y to be in the range [0,1] |
RandomSubset(n)
Signature: n:int -> Dataset
|
Sample a random subset of length |
Shuffle()
Signature: unit -> Dataset
|
Shuffle the order of elements in the dataset |
Standardize()
Signature: unit -> Dataset
|
Standardize the values in the input matrix X and output matrix Y to have zero mean and unit variance |
StandardizeX()
Signature: unit -> Dataset
|
Standardize the values in the input matrix X to have zero mean and unit variance |
StandardizeY()
Signature: unit -> Dataset
|
Standardize the values in the output matrix Y to have zero mean and unit variance |
ToSeq()
Signature: unit -> seq<DV * DV>
|
Get the input-output pairs as a sequence |
ToStringFull()
Signature: unit -> string
|
Get a string representation of this dataset showing all values |
Visualize()
Signature: unit -> string
|
Get a string visualization of this dataset |
VisualizeXColsAsImageGrid(imagerows)
Signature: imagerows:int -> string
|
Visualize the values of the input matrix X where each column will be reshaped to an image with |
VisualizeYColsAsImageGrid(imagerows)
Signature: imagerows:int -> string
|
Visualize the values of the output matrix Y where each column will be reshaped to an image with |
X
Signature: DM
|
The matrix X of input values, where columns are the individual inputs Xi |
Xi
Signature: int []
|
The index of the maximum elements of individual inputs Xi, used for one-hot representations |
Y
Signature: DM
|
The matrix Y of output values, where columns are the individual outputs Yi |
Yi
Signature: int []
|
The index of the maximum elements of individual outputs Yi, used for one-hot reprsentations |
Static member | Description |
appendBiasRowX(d)
Signature: d:Dataset -> Dataset
|
Append a row of ones to the input matrix X of dataset |
appendRowX(v d)
Signature: v:DV -> d:Dataset -> Dataset
|
Append a new row |
appendRowY(v d)
Signature: v:DV -> d:Dataset -> Dataset
|
Append a new tow |
empty
Signature: Dataset
|
The empty dataset |
isEmpty(d)
Signature: d:Dataset -> bool
|
Check whether dataset |
item(i d)
Signature: i:int -> d:Dataset -> DV * DV
|
Get the input-output pair with index |
length(d)
Signature: d:Dataset -> int
|
The length of dataset |
normalize(d)
Signature: d:Dataset -> Dataset
|
Normalize the values in the input matrix X and output matrix Y of dataset |
normalizeX(d)
Signature: d:Dataset -> Dataset
|
Normalize the values in the input matrix X of dataset |
normalizeY(d)
Signature: d:Dataset -> Dataset
|
Normalize the values in the output matrix Y of dataset |
randomSubset(n d)
Signature: n:int -> d:Dataset -> Dataset
|
Sample a random subset of length |
shuffle(d)
Signature: d:Dataset -> Dataset
|
Shuffle the order of elements in dataset |
standardize(d)
Signature: d:Dataset -> Dataset
|
Standardize the values in the input matrix X and output matrix Y of dataset |
standardizeX(d)
Signature: d:Dataset -> Dataset
|
Standardize the values in the input matrix X of dataset |
standardizeY(d)
Signature: d:Dataset -> Dataset
|
Standardize the values in the output matrix Y of dataset |
toSeq(d)
Signature: d:Dataset -> seq<DV * DV>
|
Get the input-output pairs of dataset |
toString(d)
Signature: d:Dataset -> string
|
Get a summary string of dataset |
toStringFull(d)
Signature: d:Dataset -> string
|
Get a string representation of dataset |