Download
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data with large size.
Features
- big data
- Random Bits
- neural network
- boosting
- random forest
- machine learning
- data mining
- prediction
Follow Random Bits Forest
Other Useful Business Software
Earn up to 16% annual interest with Nexo.
Put idle assets to work with competitive interest rates, borrow without selling, and trade with precision. All in one platform.
Geographic restrictions, eligibility, and terms apply.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of Random Bits Forest!
