dotnet / dotnet/machinelearning-samples

Inconsistencies between F# and C# samples

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Descrizione

We reviewed and found some inconsistencies between the C# and F# samples.
This issue is just a convenient list for having the issues in a single place so we can all take it into account while updating the F# samples in the future.

If you fix any inconsistency below, please answer this thread, so we remove it, ok?

Please see the below table comparing the execution of F# and C# samples.

Sample Name | Comments | F# sample output |  c# sample output
-- | -- | -- | --
**Credit card Fraud Detection**  | 1)Accuracy is 1 in f# sample which is not correct. 2) The way o/p is displayed is not formatted properly in f# sample. No headers, no line breaks etc 3)The probability is showing in different units for c# and f#. for ex probability =0.9993f in f# and 4.303323E-05 in C# | Trainer and Predictor:![image](https://user-images.githubusercontent.com/22335043/53192184-b0581180-35c2-11e9-91c0-4e5a0545f978.png) | Trainer:![image](https://user-images.githubusercontent.com/22335043/53192239-cf56a380-35c2-11e9-988b-fe90e66ce27e.png)Predictor: ![image](https://user-images.githubusercontent.com/22335043/53192270-e39aa080-35c2-11e9-8d71-5087d095d99e.png)
**TensorFlow Estimator** | Comment: Can see an exception in f# o/p while finding path of filel | ![image](https://user-images.githubusercontent.com/22335043/53192303-fc0abb00-35c2-11e9-826e-360ee8c8a37d.png)  |  ![image](https://user-images.githubusercontent.com/22335043/53192324-10e74e80-35c3-11e9-8a28-518e05cf67b2.png)
**Github Labeler** | Comment: Getting build error while executing github labeler sample |![image](https://user-images.githubusercontent.com/22335043/53192351-1c3a7a00-35c3-11e9-937c-7b619fb94b3c.png)  | running fine for c# sample
**TesnorFlow Scorer** | Comment: Toaster 2 and Toaster 3 are shwoing accuracy as 1 | ![image](https://user-images.githubusercontent.com/22335043/53192375-28263c00-35c3-11e9-88c2-e01b5d1b5bd7.png)  |  ![image](https://user-images.githubusercontent.com/22335043/53192385-2fe5e080-35c3-11e9-912a-973161bd8239.png)

Guida per i contributori

Apri la guida per i contributori

Direzione di ricerca

Inizia individuando gli esempi F# e C# indicati nella tabella: Credit card Fraud Detection, TensorFlow Estimator, Github Labeler e TensorFlow Scorer. Esegui gli esempi associati e confronta il loro output, gli errori, la formattazione e il comportamento della build con gli screenshot riportati. Il lavoro è concluso quando le incoerenze elencate sono state risolte e la tabella di confronto può essere aggiornata o rimossa.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Valutazione

Stack tecnologico
csharp, fsharp
Ambito
machine-learning
Tipo di issue
Bug
Difficoltà
4/5
Tempo stimato
3-5 giorni
Stato di attività
Ferma
Chiarezza
Abbastanza chiara
Idoneità per principianti
35/100

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