clustering-analysis

Deep Learning-based Clustering Approaches for Bioinformatics

Fast and Efficient Implementation of HDBSCAN in C++ using STL

Code used to identify and analyze drought clusters from gridded data.

a few different clustering algorithms with python libraries for data science

This is my toolbox for image processing and downstream analysis of calcium imaging data.

Optimize clustering labels using Silhouette Score.

Predicting Sentiment for Meme Mediterranean Restaurant Reviews: Python Scrape

This is a MATLAB implementation of the algorithm LGD presented in the following paper. Local gap density for clustering high-dimensional data. Ruijia Li, Xiaofei Yang, Xiaolong Qin, William Zhu.

Clustering Analysis of all available research data on the Iowa Gambling Task(list of sources in readme) using R. The Scripts produce the output for the most common archetypes among the dataset of one researcher using PCA.

load and visualize data and clusters with scatter plots; prepare data for cluster analysis; perform centroid clustering with k-means; interpret clustering results and determine the optimal number of clusters for a given dataset.

Random Neighbors: Random Forest style clustering for high-dimensional data

A clustering exercise of global currencies on three common financial market features using data from 2017 through 2019, as published in Towards Data Science on Medium.com

An Analysis Using DomainTools Threat Profile to Identify Risky TLDs

Solutions for different datasets in Kaggle Website

Defines a boundary around cluster centers in a given point-layer shapefile.

This is the home of my public efforts in data analytics, research and data science/software development dedicated to various aspects of COVID-19 impact analysis

It is One of the Easiest Problems in Data Science to Detect the MNIST Numbers, Using a Classification Algorithm, Here I have used a csv File which contains the Pixels of the Numbers from 0 to 9 and we have to Classify the Numbers Accordingly. I have Used K-Means Classification Algorithm.

Text Clustering for Natural Languages

An optimised implementation of the tau statistic (relative prevalence ratio form), originally from R's IDSpatialStats package.

Using single-unit/single-family residential properties sold in the Southern California area, predict Zillow's 2017 log error drivers. Use KMeans clustering techniques to uncover drivers of log error.

Internal Validity Indexes for Fuzzy and Possibilistic Clustering

COVID-19: Behind the Numbers.

Cluster Validity Index Using a Distance-based Separability Measure

Data Understanding, Visualization , Preparation & Cleaning - Clustering algorithms (unsupervised learning) - Classification algorithms (supervised learning) - Sequential Pattern Mining

This project was done together with my colleague Noam Shmuel during the class of "Unsupervised Learning" @ University of Warsaw taught by professor Jacek Lewkowicz, PhD

Nucleic Acids Research Data Discovery

NLP and clustering on movie plot summaries from IMDb and Wikipedia to quantify movie similarity.

An exploration of cervical cancer risk data using Principle Component Analysis (PCA) and clustering algorithms

Visual Assessment of Clustering Tendency for Finding the Number of Clusters in Datasets

Práctica de clustering de la asignatura Inteligencia de Negocio de cuarto curso de Ingeniería Informática.