E-commerce Data Pipeline
-
Updated
Oct 22, 2024 - Python
E-commerce Data Pipeline
Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE.
Clustering - Cohort Analysis - Retention Analysis
Library of popular algorithms implemented in a parallel way
Selection of the best centroid based clustering version with k-medoids and k-means
Implemented an auto-clustering tool with seed and number of clusters finder. Optimizing algorithms: Silhouette, Elbow. Clustering algorithms: k-Means, Bisecting k-Means, Gaussian Mixture. Module includes micro-macro pivoting, and dashboards displaying radius, centroids, and inertia of clusters. Used: Python, Pyspark, Matplotlib, Spark MLlib.
K-Means Clustering & Dimensionality Reduction and Market Basket Analysis - Project Submission for Data Mining & Machine Learning Module
code for PhD thesis
Partitioning a set of objects into groups(clusters) of diverse objects. The aim is to maximize intra-cluster diversity while at the same time maintaining the inter-cluster similarity.
An application for clustering keywords in polish based on text morphology or semantic connections.
Práctica de clustering de la asignatura Inteligencia de Negocio de cuarto curso de Ingeniería Informática.
Random Neighbors: Random Forest style clustering for high-dimensional data
Cheminformatics based project that aims to assess the diversity of the known inhibitors of SarsCov-2 proteases taken from COVID Moonshot project.
A concatenation of two GNNs to decode dynamic clustering on localization datasets
Optimize clustering labels using Silhouette Score.
Clustering and resource allocation using Deterministic Annealing Approach and Orthogonal Non-negative Matrix Factorization O-(NMF)
Defines a boundary around cluster centers in a given point-layer shapefile.
Mutual Information-based Non-linear Clustering Analysis
CRATE: Accurate and efficient clustering-based nonlinear analysis of heterogeneous materials through computational homogenization
Cluster Validity Index Using a Distance-based Separability Measure
Add a description, image, and links to the clustering-analysis topic page so that developers can more easily learn about it.
To associate your repository with the clustering-analysis topic, visit your repo's landing page and select "manage topics."