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Found 6 papers, 1 papers with code
Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data
The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods.
A Protocol for Intelligible Interaction Between Agents That Learn and Explain
In this paper we view the interaction between humans and ML systems within the broader context of interaction between agents capable of learning and explanation.
One-way Explainability Isn't The Message
We propose operational principles -- we call them Intelligibility Axioms -- to guide the design of a collaborative decision-support system.
Logical Explanations for Deep Relational Machines Using Relevance Information
We investigate the use of a Bayes-like approach to identify logical proxies for local predictions of a DRM.
B-CNN: Branch Convolutional Neural Network for Hierarchical Classification
In this way we show that CNN based models can be forced to learn successively coarse to fine concepts in the internal layers at the output stage, and that hierarchical prior knowledge can be adopted to boost CNN models' classification performance.
Word Vector Enrichment of Low Frequency Words in the Bag-of-Words Model for Short Text Multi-class Classification Problems
The bag-of-words model is a standard representation of text for many linear classifier learners.
