Active Learning for Learning to Rank (LETOR)
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Updated
Jun 30, 2016 - Java
Active Learning for Learning to Rank (LETOR)
Active Learning Project
This is our submission for the InformatiCup 2017. Although we designed our Application to assist us with the given task of classifying GitHub repositories, it should be easily reusable for other classification purposes - feel free to use it on your own!
Codebase for study measuring the effect of different sequences of active/passive input for category learning.
JCLAL is a general purpose framework developed in Java for Active Learning.
Machines and people collaborating together through Jupyter notebooks.
Cost-Effective Active Learning for Melanoma Segmentation
ALPUD: Active Learning from Positive and Unlabeled Data
Active Learning with Cross-Class Similarity Transfer
Create Dataset - a byproduct of Interactive Machine Learning.
Cost-Sensitive Multi-Class Active Learning
This presentation contains very precise yet detailed explanation of concepts of a very interesting topic -- Reinforcement Learning.
Cost-Effective Active Learning for Deep Image Classification
Graphical Interface active learning applied to GIS.
Add a description, image, and links to the active-learning topic page so that developers can more easily learn about it.
To associate your repository with the active-learning topic, visit your repo's landing page and select "manage topics."