Kianqunki's repositories
bayesian_changepoint_detection
Methods to get the probability of a changepoint in a time series.
bof_eeg
Using Bag-of-Features to classify EEG time-series data
change_point_detector
Change point detection by using density ratio estimation
ChangePointDetection
Source repository for OSDC-PIRE 2014 project on change-point detection
eo-bow
Python implementation of EO-BoW method
facets
Visualizations for machine learning datasets
Gradient-of-Mutual-Information
This project is related to the paper Communication Inspired Linear Discriminant Analysis
gramm
Gramm is a powerful visualization toolbox which allows to quickly create complex, publication-quality figures in Matlab, and is inspired by R's ggplot2 library. As a reference to this inspiration, gramm stands for GRAMmar of graphics for Matlab.
kernel_eca
Scikit-learn compatible Kernel Entropy Component Analysis in Python
LogAdvisor
Learning to Log: A framework for determining optimal logging points
logflow
Under construction
logparser
logparser: A toolkit for automated log parsing
lstm-anomaly-detect
Example code for neural-network-based anomaly detection of time-series data (uses LSTM)
malware-detection
Malware Detection and Classification Using Machine Learning
MATLAB-Online
MATLAB Online Toolbox - Create interactive charts in your web browser with MATLAB and Plotly
matlab-printfg
A collection of MATLAB functions that aim to simplify saving formatted figures for printing.
matrix-routines
Implementations of matrix factorization/completion (and something related) algorithms
pop-to-8bit
A tool for converting pop song into 8bit chiptune song.
PRMLT
Matlab code for algorithms in PRML book
pypropack
A python wrapper for the PROPACK library
python-latex-highlighting
LaTeX style for Python highlighting
Some-useful-code
Some useful code
sublime-text
sublime-text
time-series-classification-and-clustering
Time series classification and clustering code written in Python. Mostly based on the work of Dr. Eamonn Keogh at University of California Riverside
Unsupervised-Anomaly-Detection-with-Generative-Adversarial-Networks
Unsupervised Anomaly Detection with Generative Adversarial Networks on MIAS dataset