Search Packages

spade-anomaly-detection

Semi-supervised Pseudo Labeler Anomaly Detection with Ensembling (SPADE) is a semi-supervised anomaly detection method that uses an ensemble of one class classifiers as the pseudo-labelers and supervised classifiers to achieve state of the art results especially on datasets with distribution mismatch between labeled and unlabeled samples.

modssc

ModSSC: A Modular Framework for Semi Supervised Classification

sslearn

The sslearn library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.

semisupervised

Semi supervised learning framework of Python.

scnym

Semi supervised adversarial network networks for single cell classification

pypcc

Python code for the semi-supervised learning method particle competition and cooperation

semis

Semi-supervised learning methods

masksemi

Code for converting a label list in a scikit-like semi-supervised label list.