Comparison of Classification Methods for Very High-Dimensional Data in Sparse Random Projection Representation
2018
The big data trend has inspired feature-driven learning tasks, which cannot be handled by conventional machine learning models. Unstructured data produces very large binary matrices with millions of columns when converted to vector form. However, such data is often sparse, and hence can be manageable through the use of sparse random projections.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
34
References
1
Citations
NaN
KQI