Moa GitHub Repositories

Optimizing inference proxy for LLMs

A machine learning package for streaming data in Python. The other ancestor of River.

MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.

Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04

Running Mixture of Agents on CPU: LFM2.5 Brain (1.2B) + Falcon-R Reasoner (600M) + Tool Caller (90M). CPU-only, 16GB RAM. Lightweight AI Legion.

My Java codes for the MOA framework. It includes the implementations of FHDDM, FHDDMS, and MDDMs.

An external pipeline filter for Open WebUI that refactors aggregate requests with collective wisdom to output structured expert analysis reports.

Elucidate and visualise a compound's mechanism of action by combining structure-based target prediction with gene expression-based causal reasoning, plus pathway enrichment to put results into biological context. GUI-based (minimal coding experience required).

UMM-Discovery is a fully unsupervised deep learning method to cluster cellular images with similar phenotypes together, solely based on the intensity values.

iGNGSVM, OI-SVM, GNG and ENN developed in MOA/WEKA.

A streaming Digital Twin of a steel hot rolling mill demonstrating Online Machine Learning (OML) with Apache Kafka, Apache Flink and MOA to handle real-time concept drift.

A simplified agentic workflow process based on the Mixture of Agents (MoA) system for Large Language Models (LLMs)

Official repo for DK904 - IOT Stream Data Mining

Repository for the StreamingRandomPatches algorithm implemented in MOA 2019.04

Adaptive Decision Forest(ADF) is an incremental machine learning framework called to produce a decision forest to classify new records. ADF is capable to classify new records even if they are associated with previously unseen classes. ADF also is capable of identifying and handling concept drift; it, however, does not forget previously gained knowledge. Moreover, ADF is capable of handling big data if the data can be divided into batches.

MODIS Mosaic of Antarctica

Install and configure CP4I

三个臭皮匠 · 多模型智囊团 Dashboard 插件 · Mixture of Agents for Hermes Agent