Function

Static Public Summary
public	assocationRuleLearning(transactions: Array, options: Object): Object returns association rule learning results
public	getTransactions(data: Array, options: Object): Object Formats an array of transactions into a sparse matrix like format for Apriori/Eclat
public	async loadCSV(filepath: string, options: Object): Object[] Asynchronously loads a CSV from either a filepath or remote URL and returns an array of objects
public	async loadCSVURI(filepath: string, options: Object): Object[] Asynchronously loads a CSV from a remote URL and returns an array of objects
public	async loadTSV(filepath: string, options: Object): Object[] Asynchronously loads a TSV from either a filepath or remote URL and returns an array of objects

Static Public

public assocationRuleLearning(transactions: Array, options: Object): Object source

import {assocationRuleLearning} from 'modelscript/src/calc.mjs'

returns association rule learning results

Params:

Name	Type	Attribute	Description
transactions	Array		sparse matrix of transactions
options	Object
options.support	Number	optional default: 0.4	support level
options.minLength	Number	optional default: 2	minimum assocation array size
options.summary	Boolean	optional default: true	return summarized results
options.valuesMap	Map	optional default: new Map()	map of values and labels (used for summary results)

Return:

Object

Returns the result from Node-FPGrowth or a summary of support and strong associations

See:

https://github.com/alexisfacques/Node-FPGrowth

public getTransactions(data: Array, options: Object): Object source

import {getTransactions} from 'modelscript/src/calc.mjs'

Formats an array of transactions into a sparse matrix like format for Apriori/Eclat

Params:

Name	Type	Attribute	Description
data	Array		CSV data of transactions
options	Object
options.exludeEmptyTranscations	Boolean	optional default: true	exclude empty rows of transactions

Return:

Object

{values - unique list of all values, valuesMap - map of values and labels, transactions - formatted sparse array}

See:

https://github.com/alexisfacques/Node-FPGrowth

public async loadCSV(filepath: string, options: Object): Object[] source

import {loadCSV} from 'modelscript/src/csv.mjs'

Asynchronously loads a CSV from either a filepath or remote URL and returns an array of objects

Params:

Name	Type	Attribute	Description
filepath	string		URL to CSV path
options	Object	optional	options passed to csvtojson

Return:

Object[]

returns an array of objects from a csv where each column header is the property name

Example:

// returns [{header:value,header2:value2}]
loadCSV('../mock/invalid-file.csv').then(csvData).catch(console.error)

public async loadCSVURI(filepath: string, options: Object): Object[] source

import {loadCSVURI} from 'modelscript/src/csv.mjs'

Asynchronously loads a CSV from a remote URL and returns an array of objects

Params:

Name	Type	Attribute	Description
filepath	string		URL to CSV path
options	Object	optional	options passed to csvtojson

Return:

Object[]

returns an array of objects from a csv where each column header is the property name

Example:

// returns [{header:value,header2:value2}]
loadCSVURI('https://raw.githubusercontent.com/repetere/modelscript/master/test/mock/data.csv').then(csvData).catch(console.error)

public async loadTSV(filepath: string, options: Object): Object[] source

import {loadTSV} from 'modelscript/src/csv.mjs'

Asynchronously loads a TSV from either a filepath or remote URL and returns an array of objects

Params:

Name	Type	Attribute	Description
filepath	string		URL to CSV path
options	Object	optional	options passed to csvtojson

Return:

Object[]

returns an array of objects from a csv where each column header is the property name

Example:

// returns [{header:value,header2:value2}]
loadCSV('../mock/invalid-file.tsv').then(csvData).catch(console.error)