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2dhp-plot

This program can be used to plot the structure of a protein in the 2D HP model.

3d-shape-visualizer

Programa para plotagem de modelos 3D

aco-2dhp

Implementation of the Ant Colony Optimization meta-heuristic for the Protein Structure Prediction problem using 2D HP model. This approach includes the pull move heuristic for local search.

aco-tsp

Implementação do algoritmo ACO aplicado ao TSP

angularjs-data-binding

Binding ng-model inside ng-repeat loop in AngularJS

anynovel

This is an implementation of AnyNovel Algorithm for detetcing novel concepts in evloving data streams. Paper can be found here https://link.springer.com/article/10.1007/s12530-016-9147-7

arm-cdsc-al

arm-stream-framework

ARM-Stream: Active Recovery of Miscategorizations in Clustering-Based Data Stream Classifiers

asterisk-jtapi

CVS repository from https://sourceforge.net/p/asterisk-jtapi/code/

athena-client

birch

C implementation of the BIRCH algorithm, an unsupervised data mining algorithm which is used to perform hierarchical clustering over particularly large data-sets.

cdsc-al

A Clustering-based Data Stream Classification framework using Active Learning

convolutional-net-prototype-ensemble

implement of ICDE 2019 paper: Robust High Dimensional Stream Classification with Novel Class Detection

data-stream-env

Strategies based on active learning and semi supervised learning for classification, novelty detection and concept drift detection over data streams.

download-using-streaming-response-body

An example for streaming large files in chunks using StreamingResponseBody in Spring MVC

ds-framework

Framework for data stream classifier algorithms

echo

Semi-supervised framework for classifying evolving data streams

echo-original

ECHO is a semi-supervised framework for classifying evolving data streams based on our previous approach SAND. The most expensive module of SAND is the change detection module, which has cubic time complexity. ECHO uses dynamic programming to reduce the time complexity. Moreover, ECHO has a maximum allowable sliding window size. If there is no concept drift detected within this limit, ECHO updates the classifiers and resets the sliding window. Experiment results show that ECHO achieves significant speed up over SAND while maintaining similar accuracy. Please refer to the paper (mentioned in the reference section) for further details.

go-topic

higia

data streams, incremental clustering, novelty detection, concept drift

jbirch

Automatically exported from code.google.com/p/jbirch

kmeans-hadoop

data mining discipline project

lazy-matrix

Matrix with polynomial initialization

md2018

Repositórios da Disciplina GBC212 - Mineração de Dados

minas

PCF compatible MINAS (MultI-class learNing Algorithm for data Streams). An algorithm to address novelty detection in data streams multi-class problems.

minas-reference-implementation

Reference implementation for MINAS (MultI-class learNing Algorithm for data Streams), an algorithm to address novelty detection in data streams multi-class problems.

mltk

Machine learning toolkit

moa

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.

newsriver

A continuous feed of news you care about

novelty-detection-env