Comments (13)
Hi @alexbogun,
Currently the data I/O logic expects the input files to exclude the index column with an empty column name. Could you try removing the first column in your files, or adding the index=False
flag if you are using pandas to prepare the input files?
I've created #106 to improve the data validation experience.
from manifold.
same issue
from manifold.
@Casyfill tried that, does not work either
from manifold.
Let me investigate this
from manifold.
actually sorry, it worked for me once I've added column names for Ypred and Ytrue
from manifold.
OK gotcha. I'll close this issue for now. Please reach out to us if you're still experiencing the same issue.
from manifold.
What did you do differently than in the attached 3 files, I have column names there as well? Please do not close this yet.
from manifold.
Hi @gnavvy ,
Thank you very much for your help, the issue where indeed the index columns.
Adding error message would indeed be a great improvement.
But if I may suggest also to modify the images in section on preparing data, because I was sure I had to include index based on those.
Thanks again, I will close this one, since you started #106
from manifold.
Hi, sorry to have to bother you again, but now I cannot figure out how to upload multiple predictions, when I upload only one of the predictions it works, but when I upload both it does not...
Files used:
prediction1.txt
prediction2.txt
truth.txt
features.txt
from manifold.
from manifold.
I have tried adding multiple predictions as well without success. When I upload two prediction csv with the same format / no index I get this error:
Error: yPred[1][0] has a different shape than other element in yPred. Check your input data.
I've verified both are the same shape however. Also the data loads successful if I include one or the other prediction.csv files by themselves, just not when I add both files at the same time.
from manifold.
@sar2160 Could you share the files that caused the issues? And are you using the website or running the application locally?
from manifold.
from manifold.
Related Issues (20)
- Jupyter notebook - Export Segmentation not working HOT 2
- Module not found error HOT 1
- Segmentation by difference between models' performance
- Support multi-class classification HOT 1
- Allow users to change model names
- Allow users to monitor and change feature types
- Add on-screen tooltips
- Create practical examples using public datasets HOT 1
- Performance metric drop down not working and explanation of feature attribution is not clear HOT 1
- Export report
- Not obvious distributions for categorical features HOT 2
- How to prepare prediction dataset for manifold HOT 1
- Improve "Running demo app locally"
- CSV upload of large data does not work.
- Demo sample data is not working HOT 1
- Python manifold provide alias to model name
- Drill down to data points in clusters HOT 1
- are you planning to create python version ?
- URL does not load HOT 3
- your github.io domain seems to have been hijacked HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from manifold.