Documentation ¶
Index ¶
- type AbstractDiscretizeFilter
- type BinaryConvertFilter
- func (b *BinaryConvertFilter) AddAttribute(a base.Attribute) error
- func (b *BinaryConvertFilter) GetAttributesAfterFiltering() []base.FilteredAttribute
- func (b *BinaryConvertFilter) String() string
- func (b *BinaryConvertFilter) Train() error
- func (b *BinaryConvertFilter) Transform(a base.Attribute, n base.Attribute, attrBytes []byte) []byte
- type BinningFilter
- type ChiMergeFilter
- type FloatConvertFilter
- func (f *FloatConvertFilter) AddAttribute(a base.Attribute) error
- func (f *FloatConvertFilter) GetAttributesAfterFiltering() []base.FilteredAttribute
- func (f *FloatConvertFilter) String() string
- func (f *FloatConvertFilter) Train() error
- func (f *FloatConvertFilter) Transform(a base.Attribute, n base.Attribute, attrBytes []byte) []byte
- type FrequencyTableEntry
Constants ¶
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Variables ¶
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Functions ¶
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Types ¶
type AbstractDiscretizeFilter ¶
type AbstractDiscretizeFilter struct {
// contains filtered or unexported fields
}
func (*AbstractDiscretizeFilter) AddAttribute ¶
func (d *AbstractDiscretizeFilter) AddAttribute(a base.Attribute) error
AddAttribute adds the AttributeSpec of the given attribute `a' to the AbstractFloatFilter for discretisation.
func (*AbstractDiscretizeFilter) GetAttributesAfterFiltering ¶
func (d *AbstractDiscretizeFilter) GetAttributesAfterFiltering() []base.FilteredAttribute
GetAttributesAfterFiltering gets a list of before/after Attributes as base.FilteredAttributes
type BinaryConvertFilter ¶
type BinaryConvertFilter struct {
// contains filtered or unexported fields
}
BinaryConvertFilters convert a given DataGrid into one which only contains BinaryAttributes.
FloatAttributes are discretised into either 0 (if the value is 0) or 1 (if the value is not 0).
CategoricalAttributes are discretised into one or more new BinaryAttributes.
func NewBinaryConvertFilter ¶
func NewBinaryConvertFilter() *BinaryConvertFilter
NewBinaryConvertFilter creates a blank BinaryConvertFilter
func (*BinaryConvertFilter) AddAttribute ¶
func (b *BinaryConvertFilter) AddAttribute(a base.Attribute) error
AddAttribute adds a new Attribute to this Filter
func (*BinaryConvertFilter) GetAttributesAfterFiltering ¶
func (b *BinaryConvertFilter) GetAttributesAfterFiltering() []base.FilteredAttribute
GetAttributesAfterFiltering returns the Attributes previously computed via Train()
func (*BinaryConvertFilter) String ¶
func (b *BinaryConvertFilter) String() string
String gets a human-readable string
func (*BinaryConvertFilter) Train ¶
func (b *BinaryConvertFilter) Train() error
Train converts the FloatAttributesinto equivalently named BinaryAttributes, leaves BinaryAttributes unmodified and processes CategoricalAttributes as follows.
If the CategoricalAttribute has two values, one of them is designated 0 and the other 1, and a single identically-named binary Attribute is returned.
If the CategoricalAttribute has more than two (n) values, the Filter generates n BinaryAttributes and sets each of them if the value's observed.
func (*BinaryConvertFilter) Transform ¶
func (b *BinaryConvertFilter) Transform(a base.Attribute, n base.Attribute, attrBytes []byte) []byte
Transform converts the given byte sequence using the old Attribute into the new byte sequence.
If the old Attribute has a categorical value of at most two items, then a zero or non-zero byte sequence is returned.
If the old Attribute has a categorical value of at most n-items, then a non-zero or zero byte sequence is returned based on the value of the new Attribute passed in.
If the old Attribute is a float, it's value's unpacked and we check for non-zeroness ¶
If the old Attribute is a BinaryAttribute, just return the input
type BinningFilter ¶
type BinningFilter struct { AbstractDiscretizeFilter // contains filtered or unexported fields }
BinningFilter does equal-width binning for numeric Attributes (aka "histogram binning")
func NewBinningFilter ¶
func NewBinningFilter(d base.FixedDataGrid, bins int) *BinningFilter
NewBinningFilter creates a BinningFilter structure with some helpful default initialisations.
func (*BinningFilter) GetAttributesAfterFiltering ¶
func (b *BinningFilter) GetAttributesAfterFiltering() []base.FilteredAttribute
GetAttributesAfterFiltering gets a list of before/after Attributes as base.FilteredAttributes
func (*BinningFilter) String ¶
func (b *BinningFilter) String() string
func (*BinningFilter) Train ¶
func (b *BinningFilter) Train() error
Train computes and stores the bin values for the training instances.
type ChiMergeFilter ¶
type ChiMergeFilter struct { AbstractDiscretizeFilter Significance float64 MinRows int MaxRows int // contains filtered or unexported fields }
ChiMergeFilter implements supervised discretisation by merging successive numeric intervals if the difference in their class distribution is not statistically signficant. See Bramer, "Principles of Data Mining", 2nd Edition
pp 105--115
func NewChiMergeFilter ¶
func NewChiMergeFilter(d base.FixedDataGrid, significance float64) *ChiMergeFilter
NewChiMergeFilter creates a ChiMergeFilter with some helpful intialisations.
func (*ChiMergeFilter) GetAttributesAfterFiltering ¶
func (c *ChiMergeFilter) GetAttributesAfterFiltering() []base.FilteredAttribute
GetAttributesAfterFiltering gets a list of before/after Attributes as base.FilteredAttributes
func (*ChiMergeFilter) String ¶
func (c *ChiMergeFilter) String() string
func (*ChiMergeFilter) Train ¶
func (c *ChiMergeFilter) Train() error
type FloatConvertFilter ¶
type FloatConvertFilter struct {
// contains filtered or unexported fields
}
FloatConvertFilters convert a given DataGrid into one which only contains BinaryAttributes.
FloatAttributes are discretised into either 0 (if the value is 0) or 1 (if the value is not 0).
CategoricalAttributes are discretised into one or more new BinaryAttributes.
func NewFloatConvertFilter ¶
func NewFloatConvertFilter() *FloatConvertFilter
NewFloatConvertFilter creates a blank FloatConvertFilter
func (*FloatConvertFilter) AddAttribute ¶
func (f *FloatConvertFilter) AddAttribute(a base.Attribute) error
AddAttribute adds a new Attribute to this Filter
func (*FloatConvertFilter) GetAttributesAfterFiltering ¶
func (f *FloatConvertFilter) GetAttributesAfterFiltering() []base.FilteredAttribute
GetAttributesAfterFiltering returns the Attributes previously computed via Train()
func (*FloatConvertFilter) String ¶
func (f *FloatConvertFilter) String() string
String gets a human-readable string
func (*FloatConvertFilter) Train ¶
func (f *FloatConvertFilter) Train() error
Train converts the Attributes into equivalently named FloatAttributes, leaves FloatAttributes unmodified and processes CategoricalAttributes as follows.
If the CategoricalAttribute has two values, one of them is designated 0.0 and the other 1.0, and a single identically-named FloatAttribute is returned.
If the CategoricalAttribute has more than two (n) values, the Filter generates n FloatAttributes and sets each of them if the value's observed.
type FrequencyTableEntry ¶
func ChiMBuildFrequencyTable ¶
func ChiMBuildFrequencyTable(attr base.Attribute, inst base.FixedDataGrid) []*FrequencyTableEntry
func (*FrequencyTableEntry) String ¶
func (t *FrequencyTableEntry) String() string