ImputeDistances

Machine learning based imputation techniques for estimating phylogenetic trees from incomplete distance matrices | We introduce two highly accurate machine learning based distance imputation techniques. One of our approaches is based on matrix factorization (MatrixFactorization.py), and the other one is an autoencoder based deep learning technique (Autoencoder.py). We evaluate these two techniques on a collection of simulated and biological datasets, and show that our techniques are more accurate and robust than the best alternate technique for distance imputation. Moreover, our proposed techniques can handle substantial amount of missing data, to the extent where the best alternate method fails | (See the imports in both of the python files) | -python 3.5+ -easygui -pandas -numpy -matplotlib -seaborn -tensorflow -keras