Name
Abstract | ||
|---|---|---|
BrainCel is an interactive visual system for performing general-purpose machine learning in spreadsheets, building on end-user programming and interactive machine learning. BrainCel features multiple coordinated views of the model being built, explaining its current confidence in predictions as well as its coverage of the input domain, thus helping the user to evolve the model and select training examples. Through a study investigating users' learning barriers while building models using BrainCel, we found that our approach successfully complements the Teach and Try system [1] to facilitate more complex modelling activities. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/VLHCC.2015.7357211 | 2015 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) |
Keywords | Field | DocType |
interactive visual machine learning,spreadsheets,general-purpose machine learning,end-user programming,BrainCel,input domain,training example selection,user learning barriers,Teach-and-Try system,complex modelling activities | Robot learning,Algorithmic learning theory,Instance-based learning,Numerical models,Active learning (machine learning),Computer science,Hyper-heuristic,Human–computer interaction,Artificial intelligence,Computational learning theory,Artificial neural network,Machine learning | Conference |
Citations | PageRank | References |
5 | 0.51 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Advait Sarkar | 1 | 22 | 4.64 |
| Mateja Jamnik | 2 | 158 | 30.79 |
| Alan F. Blackwell | 3 | 2042 | 177.34 |
| Martin Spott | 4 | 71 | 14.53 |