MEX Core (mex-core) is an ontology with the goal of describing the core process for machine learning problems (MEX Platform)

Classes

adaptative web sites
affective computing
application context
bioinformatics
bootstrapping
brain machine interfaces
cheminformatics
classifying d n asequences
computational adversiting
computational finance
computer vision
context
cross validation
dataset
detecting credit card frauds
domain concept space
example
example collection
execution
execution overall
execution single
experiment
experiment configuration
fact prediction
feature
feature collection
game playing
hardware configuration
holdout
information retrieval
internet fraud detection
leave one out
link discovery
machine perception
medical diagnosis
metaheuristics
model
n folds cross validation
natural language processing
object recognition
optimization
phase
recomender systems
robotics
sampling method
search engines
sentiment analysis
sequence mining
sliding cross validation
software engineering
speech and handwriting recognition
stock market analysis
structural health monitoring
syntactic language processing
test
training
validation

adaptative web sites^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#AdaptativeWebSites

has super-classes: context^c

affective computing^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#AffectiveComputing

has super-classes: context^c

application context^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ApplicationContext

describes the context of the experiment, such as NLP, Stock Market Forecast, BioInformatics, Text-Retrieval AND contact informations/publication

has super-classes: domain concept space^c; agent^c; organization^c; person^c
is in domain of: trusty u r i^op, trusty u r i hash^dp
is in range of: has application context^op

bioinformatics^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Bioinformatics

has super-classes: context^c

bootstrapping^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Bootstrapping

has super-classes: sampling method^c

brain machine interfaces^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#BrainMachineInterfaces

has super-classes: context^c

cheminformatics^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Cheminformatics

has super-classes: context^c

classifying d n asequences^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ClassifyingDNAsequences

has super-classes: context^c

computational adversiting^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ComputationalAdversiting

has super-classes: context^c

computational finance^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ComputationalFinance

has super-classes: context^c

computer vision^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ComputerVision

has super-classes: context^c

context^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Context

has super-classes: domain concept space^c; entity^c
has sub-classes: adaptative web sites^c, affective computing^c, bioinformatics^c, brain machine interfaces^c, cheminformatics^c, classifying d n asequences^c, computational adversiting^c, computational finance^c, computer vision^c, detecting credit card frauds^c, fact prediction^c, game playing^c, information retrieval^c, internet fraud detection^c, link discovery^c, machine perception^c, medical diagnosis^c, metaheuristics^c, natural language processing^c, object recognition^c, optimization^c, recomender systems^c, robotics^c, search engines^c, sentiment analysis^c, sequence mining^c, software engineering^c, speech and handwriting recognition^c, stock market analysis^c, structural health monitoring^c, syntactic language processing^c

cross validation^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#CrossValidation

has super-classes: sampling method^c

dataset^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Dataset

has super-classes: domain concept space^c; entity^c

Class that provides a structured dataset

detecting credit card frauds^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#DetectingCreditCardFrauds

has super-classes: context^c

domain concept space^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#DomainConceptSpace

has sub-classes: application context^c, context^c, dataset^c, example collection^c, execution^c, experiment^c, experiment configuration^c, hardware configuration^c, model^c, sampling method^c
is disjoint with: value partition^c

example^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Example

has super-classes: entity^c
is in domain of: dataset column^op, dataset row^op

example collection^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ExampleCollection

has super-classes: domain concept space^c; collection^c
is in domain of: ends at^op, has phase^op, starts at^op

execution^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Execution

has super-classes: domain concept space^c; activity^c
has sub-classes: execution overall^c, execution single^c
is in domain of: ends at position^dp, target class^dp

execution overall^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ExecutionOverall

has super-classes: execution^c

execution single^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ExecutionSingle

has super-classes: execution^c

experiment^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Experiment

has super-classes: domain concept space^c; entity^c
is in domain of: attribute selection description^dp, data normalized description^dp, has sampling method^op, noise removed description^dp, outliers removed description^dp

experiment configuration^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ExperimentConfiguration

has super-classes: domain concept space^c; activity^c

fact prediction^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#FactPrediction

has super-classes: context^c

feature^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Feature

has super-classes: entity^c

feature collection^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#FeatureCollection

has super-classes: collection^c

game playing^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#GamePlaying

has super-classes: context^c

hardware configuration^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#HardwareConfiguration

has super-classes: domain concept space^c; version; entity^c
is in domain of: cpu^dp, cpu cache^dp, hd type^dp, memory^dp, video graphs^dp

holdout^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Holdout

has super-classes: sampling method^c

information retrieval^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#InformationRetrieval

has super-classes: context^c

internet fraud detection^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#InternetFraudDetection

has super-classes: context^c

leave one out^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#LeaveOneOut

has super-classes: sampling method^c

link discovery^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#LinkDiscovery

has super-classes: context^c

machine perception^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#MachinePerception

has super-classes: context^c

medical diagnosis^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#MedicalDiagnosis

has super-classes: context^c

metaheuristics^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Metaheuristics

has super-classes: context^c

model^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Model

has super-classes: domain concept space^c; entity^c

n folds cross validation^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#NFoldsCrossValidation

has super-classes: sampling method^c

natural language processing^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#NaturalLanguageProcessing

has super-classes: context^c

object recognition^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#ObjectRecognition

has super-classes: context^c

optimization^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Optimization

has super-classes: context^c

phase^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Phase

is equivalent to: test^c or training^c or validation^c
has super-classes: value partition^c; entity^c
has sub-classes: test^c, training^c, validation^c
is in range of: has phase^op

recomender systems^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#RecomenderSystems

has super-classes: context^c

robotics^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Robotics

has super-classes: context^c

sampling method^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#SamplingMethod

has super-classes: domain concept space^c; entity^c
has sub-classes: bootstrapping^c, cross validation^c, holdout^c, leave one out^c, n folds cross validation^c, sliding cross validation^c
is in domain of: folds^dp, sequential^dp, test size^dp, train size^dp

search engines^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#SearchEngines

has super-classes: context^c

sentiment analysis^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#SentimentAnalysis

has super-classes: context^c

sequence mining^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#SequenceMining

has super-classes: context^c

sliding cross validation^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#SlidingCrossValidation

has super-classes: sampling method^c
is in domain of: number of iteraction^dp

software engineering^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#SoftwareEngineering

has super-classes: context^c

speech and handwriting recognition^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#SpeechAndHandwritingRecognition

has super-classes: context^c

stock market analysis^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#StockMarketAnalysis

has super-classes: context^c

structural health monitoring^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#StructuralHealthMonitoring

has super-classes: context^c

syntactic language processing^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#SyntacticLanguageProcessing

has super-classes: context^c

test^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Test

has super-classes: phase^c
is disjoint with: training^c, validation^c

training^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Training

has super-classes: phase^c
is disjoint with: test^c, validation^c

validation^c back to ToC or Class ToC

IRI: http://mex.aksw.org/mex-core#Validation

has super-classes: phase^c
is disjoint with: test^c, training^c

Data Properties

attribute selection description
cpu
cpu cache
data normalized description
ends at position
folds
hd type
memory
noise removed description
number of iteraction
outliers removed description
sequential
target class
test size
train size
trusty u r i hash
video graphs

attribute selection description^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#attributeSelectionDescription

has domain: experiment^c
has range: string

cpu^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#cpu

has domain: hardware configuration^c
has range: string

cpu cache^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#cpuCache

has domain: hardware configuration^c
has range: string

data normalized description^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#dataNormalizedDescription

has domain: experiment^c
has range: string

ends at position^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#endsAtPosition

has domain: execution^c
has range: string

folds^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#folds

has domain: sampling method^c
has range: non negative integer

hd type^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#hdType

has domain: hardware configuration^c
has range: string

memory^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#memory

has domain: hardware configuration^c
has range: string

noise removed description^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#noiseRemovedDescription

has domain: experiment^c
has range: string

number of iteraction^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#numberOfIteraction

has domain: sliding cross validation^c
has range: non negative integer

outliers removed description^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#outliersRemovedDescription

has domain: experiment^c
has range: string

sequential^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#sequential

has domain: sampling method^c
has range: boolean

target class^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#targetClass

has domain: execution^c
has range: string

test size^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#testSize

has domain: sampling method^c
has range: double

train size^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#trainSize

has domain: sampling method^c
has range: double

trusty u r i hash^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#trustyURIHash

has characteristics: functional

has domain: application context^c
has range: string

video graphs^dp back to ToC or Data Property ToC

IRI: http://mex.aksw.org/mex-core#videoGraphs

has domain: hardware configuration^c
has range: string

This HTML document was obtained by processing the OWL ontology source code through LODE, Live OWL Documentation Environment, developed by Silvio Peroni.

MEX Core (mex-core) is an ontology with the goal of describing the core process for machine learning problems (MEX Platform)

Abstract

Table of Content

Classes

adaptative web sitesc back to ToC or Class ToC

affective computingc back to ToC or Class ToC

application contextc back to ToC or Class ToC

bioinformaticsc back to ToC or Class ToC

bootstrappingc back to ToC or Class ToC

brain machine interfacesc back to ToC or Class ToC

cheminformaticsc back to ToC or Class ToC

classifying d n asequencesc back to ToC or Class ToC

computational adversitingc back to ToC or Class ToC

computational financec back to ToC or Class ToC

computer visionc back to ToC or Class ToC

contextc back to ToC or Class ToC

cross validationc back to ToC or Class ToC

datasetc back to ToC or Class ToC

detecting credit card fraudsc back to ToC or Class ToC

domain concept spacec back to ToC or Class ToC

examplec back to ToC or Class ToC

example collectionc back to ToC or Class ToC

executionc back to ToC or Class ToC

execution overallc back to ToC or Class ToC

execution singlec back to ToC or Class ToC

experimentc back to ToC or Class ToC

experiment configurationc back to ToC or Class ToC

fact predictionc back to ToC or Class ToC

featurec back to ToC or Class ToC

feature collectionc back to ToC or Class ToC

game playingc back to ToC or Class ToC

hardware configurationc back to ToC or Class ToC

holdoutc back to ToC or Class ToC

information retrievalc back to ToC or Class ToC

internet fraud detectionc back to ToC or Class ToC

leave one outc back to ToC or Class ToC

link discoveryc back to ToC or Class ToC

machine perceptionc back to ToC or Class ToC

medical diagnosisc back to ToC or Class ToC

metaheuristicsc back to ToC or Class ToC

modelc back to ToC or Class ToC

n folds cross validationc back to ToC or Class ToC

natural language processingc back to ToC or Class ToC

object recognitionc back to ToC or Class ToC

optimizationc back to ToC or Class ToC

phasec back to ToC or Class ToC

recomender systemsc back to ToC or Class ToC

roboticsc back to ToC or Class ToC

sampling methodc back to ToC or Class ToC

search enginesc back to ToC or Class ToC

sentiment analysisc back to ToC or Class ToC

sequence miningc back to ToC or Class ToC

sliding cross validationc back to ToC or Class ToC

software engineeringc back to ToC or Class ToC

speech and handwriting recognitionc back to ToC or Class ToC

stock market analysisc back to ToC or Class ToC

structural health monitoringc back to ToC or Class ToC

syntactic language processingc back to ToC or Class ToC

testc back to ToC or Class ToC

trainingc back to ToC or Class ToC

validationc back to ToC or Class ToC

Object Properties

dataset columnop back to ToC or Object Property ToC

dataset rowop back to ToC or Object Property ToC

ends atop back to ToC or Object Property ToC

has application contextop back to ToC or Object Property ToC

has phaseop back to ToC or Object Property ToC

has sampling methodop back to ToC or Object Property ToC

starts atop back to ToC or Object Property ToC

trusty u r iop back to ToC or Object Property ToC