This repo is tutorial for exploring various algorithms for Multi-output prediction in ML and DL using a regressor data and understanding them how mathematically they work.
I have explored: Machine learning algorithms
- for which the multi-output available as default:
- Linear regression
- KNN Regressor
- Decision Tree Regressor.
- Random forest.
- Also, Explored methods that can be used with Algorithms which doesn't support multi-output
- Chain
- Direct using SVM
Deep learning algorithms:
- Simple Feed-forward Neural network