lnsmote

package
v0.2.0 Latest Latest
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Published: Jun 16, 2016 License: BSD-3-Clause Imports: 8 Imported by: 0

Documentation

Overview

Package lnsmote implement the Local-Neighborhood algorithm from the paper,

Maciejewski, Tomasz, and Jerzy Stefanowski. "Local neighbourhood
extension of SMOTE for mining imbalanced data." Computational
Intelligence and Data Mining (CIDM), 2011 IEEE Symposium on. IEEE,
2011.

Index

Constants

This section is empty.

Variables

View Source
var (
	// DEBUG debug level, set from environment.
	DEBUG = 0
)

Functions

This section is empty.

Types

type Runtime added in v0.2.0

type Runtime struct {
	// Runtime of SMOTE, since this module extend the SMOTE method.
	smote.Runtime

	// ClassMinor the minority sample in dataset that we want to
	// oversampling.
	ClassMinor string `json:"ClassMinor"`

	// OutliersFile if its not empty then outliers will be saved in file
	// specified by this option.
	OutliersFile string `json:"OutliersFile"`
	// contains filtered or unexported fields
}

Runtime parameters for input and output.

func New added in v0.2.0

func New(percentOver, k, classIndex int, classMinor, outliers string) (
	lnsmoteRun *Runtime,
)

New create and return new LnSmote object.

func (*Runtime) Init added in v0.2.0

func (in *Runtime) Init(dataset tabula.ClasetInterface)

Init will initialize LNSmote runtime by checking input values and set it to default if not set or invalid.

func (*Runtime) Resampling added in v0.2.0

func (in *Runtime) Resampling(dataset tabula.ClasetInterface) (
	e error,
)

Resampling will run resampling process on dataset and return the synthetic samples.

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