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GitHub / mallikabr / Machine-Learning
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mallikabr%2FMachine-Learning
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Forks: 0
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License: None
Language: Jupyter Notebook
Repo Size: 5.86 MB
Dependencies:
92
Created: about 1 year ago
Updated: 9 months ago
Last pushed: 9 months ago
Last synced: 9 months ago
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Dependencies
- APrinttotalnumberofsamplesinthevalidationdataset *
- AgainafollowupofTasksOandP *
- Assignment1 *
- BPrinttwonumbersintheformat *
- Background *
- CPrintstandarddeviationofthesecondfeature *
- DPrintmedian *
- DatasetDescription *
- DivisionbyZeroerror ,return
- ECompletethefunction *
- FN ,TP
- FYouneedtocompletetheaccuracyfunctionpartiallydefinedinthefile *
- FlipthepredictionofModel1 ,andthencomputeand
- GYouneedtocompletetheprecisionfunctionpartiallydefinedinthefile *
- HYouneedtocompletetherecallfunctionpartiallydefinedinthefile *
- IYouneedtocompletetheF1functionpartiallydefinedinthefilethat *
- Inthe *
- JYouneedtocompletetheMCCfunctiondefinedinthefilethattakesa *
- KYouneedtocompletetheFDRfunctiondefinedinthefilethattakesa *
- LPrintasadataframecontaining *
- MPrintthemodelnamewithpathwhichisperformingsuperioramong *
- NPrintthemodelnamewithpathwhichisperformingtheworstamong *
- Non-codingRNAs *
- Now ,flipthepredictions,i.e.,positivesarenowwillbepredictedasnegative,andnegativesaregoingtobepredictedaspositive.Then,computeF1_flippedandMCC_flipped,denotingcorrespondingF1andMCCscores.Returnthenew
- OScaleallthefeaturesofthevalidationsetusingtheformula ,z=
- PPrintasadataframecontaining *
- Pleasecommentonwhichofthesixmodelsisthebestonthecostbasis. *
- Pleasecommentonwhichofthesixmodelsisthebestoverall.Explainyouranswer. *
- PredictiveValue *
- Printthemodelnamewithpathwhichisperformingsuperiorintermsofaccuracy ,giventheperformanceresultdataframefrom
- Printthemodelnamewithpathwhichisperformingtheworstintermsofrecall ,giventheperformanceresultdataframefrom
- QPrintthemodelnamewithpathwhichisperformingsuperiorinterms *
- RPrintthemodelnamewithpathwhichisperformingtheworstinterms *
- Say ,inaconfusionmatrix,thevaluesofthefourmetricsare
- SixmoretasksForGraduateStudentsonly *
- Storethescaleddatasetinavariable *
- TP *
- ThistaskisafollowupofTaskP.Thereisalwayscostassociatedwithmisclassifications.Forinstance ,ifamodelpredictsancRNA
- TruePositiveRate *
- Whatisthecostofpredictionswitheachofthesixmodels *
- andrecall.IncaseofDivisionbyZeroerror ,return
- biologicalknowledge ,machinelearningmethodsthatcanaccuratelydetectncRNAsinsequenced
- confusionmatrix ,i.e.thelistofthefourmetrics
- data *
- dataframefrom *
- discovered.However ,itisdifficulttodetectnovelncRNAsinbiochemicalscreens.Toadvance
- error ,return
- for *
- frequenciesofsequence2 *
- genomesarethereforedesirable.Inthisassignment ,youwillbeexploringthedatawithstructural
- informationoftheRNAmoleculestounderstandandevaluate6pre-trainedclassifiersstoredinyour *
- inmodel_files *
- metrics *
- molecules ,andtheirgroundtruthclasslabelsasabove.
- moleculesandthegroundtruthclasslabels *
- n0representsnumberofclass =0
- numberofclass =1
- oFeature1 *
- oFeature2 *
- oFeature3 *
- oFeature4 *
- oFeature5 *
- oFeature6 *
- oFeature7 *
- oFeature8 *
- oTheentiretrainingdatasetwasusedtodevelopthe6models *
- ofaccuracy ,giventheperformanceresultdataframefrom
- ofrecall ,giventheperformanceresultdataframefrom
- ontheoriginal *
- order ,andreturnFalseDiscoveryRate
- order ,andreturnMatthewsCorrelationCoefficient
- printasadataframecontaining *
- projectdirectory *
- resultdataframefrom *
- samplesinthevalidationset *
- sequence *
- shape *
- takesaconfusionmatrix ,i.e.thelistofthefourmetrics
- thattakesaconfusionmatrix ,i.e.thelistofthefourmetrics
- the6pretrainedmodelsintermsofaccuracy ,giventheperformance
- the6pretrainedmodelsintermsofrecall ,giventheperformanceresult
- thelengthofboththearrays.Thefunctionshouldreturnalistof4 *
- truthclasslabelsandpredictedclasslabelsfortheNsampleswhenNis *
- twoarraysoftargetvariable *
- wherem =meanofafeatureinthetrainingset
- Here ,youwillfindthenamesofthe37variablesusedinthedatasetabove.And,thesourceofthedatasetdidnotoffermedescriptionofeverysingleofthem.But,afterstudyingaboutthem,Icouldelaborateonlyfewofthem.Pleasepardonmylaziness.Okay,thisfilecontainsfewdescriptionsforthevariables.AlltherestaremostlytalkingabouttheMother
- Ithas101400rows *
- The *
- Thisisaninterestingfile.Itcontainsnewsamples *
- baby-weights-dataset.csv *
- data-description.txt *
- judge-without-labels.csv *