DFFML provides APIs for dataset generation and storage, and model definition using any machine learning framework, from high level down to low level use is supported. As the goal of DFFML is to build a community driven library of plugins for dataset generation and model definition, so that developers and researchers easily plug and play various pieces of data with various model implementations or generate datasets using the implemented features to increase the accuracy of output. For this, DFFML needs to implement large number of machine learning models as well as various features. I have planned to add the below listed Models/Algorithms to DFFML.
- Model 1: Ordinary Least Square Regression (OLSR)
- Model 2: Logistic Regression
- Model 3: k-Nearest Neighbour (kNN)
- Model 4: Naive Bayes