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Types ¶
type BinningFilter ¶
type BinningFilter struct { Attributes []int Instances *base.Instances BinCount int MinVals map[int]float64 MaxVals map[int]float64 // contains filtered or unexported fields }
BinningFilter does equal-width binning for numeric Attributes (aka "histogram binning")
func NewBinningFilter ¶
func NewBinningFilter(inst *base.Instances, bins int) BinningFilter
NewBinningFilter creates a BinningFilter structure with some helpful default initialisations.
func (*BinningFilter) AddAllNumericAttributes ¶
func (b *BinningFilter) AddAllNumericAttributes()
AddAllNumericAttributes adds every suitable attribute to the BinningFilter for discretiation
func (*BinningFilter) AddAttribute ¶
func (b *BinningFilter) AddAttribute(a base.Attribute)
AddAttribute adds the index of the given attribute `a' to the BinningFilter for discretisation.
func (*BinningFilter) Build ¶
func (b *BinningFilter) Build()
Build computes and stores the bin values for the training instances.
func (*BinningFilter) Run ¶
func (b *BinningFilter) Run(on *base.Instances)
Run applies a trained BinningFilter to a set of Instances, discretising any numeric attributes added.
IMPORTANT: Run discretises in-place, so make sure to take a copy if the original instances are still needed
IMPORTANT: This function panic()s if the filter has not been trained. Call Build() before running this function
IMPORTANT: Call Build() after adding any additional attributes. Otherwise, the training structure will be out of date from the values expected and could cause a panic.
type ChiMergeFilter ¶
type ChiMergeFilter struct { Attributes []int Instances *base.Instances Tables map[int][]*FrequencyTableEntry 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(inst *base.Instances, significance float64) ChiMergeFilter
Create a ChiMergeFilter with some helpful intialisations.
func (*ChiMergeFilter) AddAllNumericAttributes ¶
func (b *ChiMergeFilter) AddAllNumericAttributes()
AddAllNumericAttributes adds every suitable attribute to the ChiMergeFilter for discretisation
func (*ChiMergeFilter) AddAttribute ¶
func (c *ChiMergeFilter) AddAttribute(attr base.Attribute)
AddAttribute add a given numeric Attribute `attr' to the filter.
IMPORTANT: This function panic()s if it can't locate the attribute in the Instances set.
func (*ChiMergeFilter) Build ¶
func (c *ChiMergeFilter) Build()
Build trains a ChiMergeFilter on the ChiMergeFilter.Instances given
func (*ChiMergeFilter) Run ¶
func (c *ChiMergeFilter) Run(on *base.Instances)
Run discretises the set of Instances `on'
IMPORTANT: ChiMergeFilter discretises in place.
type FrequencyTableEntry ¶
func ChiMBuildFrequencyTable ¶
func ChiMBuildFrequencyTable(attr int, inst *base.Instances) []*FrequencyTableEntry
func (*FrequencyTableEntry) String ¶
func (t *FrequencyTableEntry) String() string