There are 0 repository under optics-clustering topic.
Fast OPTICS clustering in Cython + gradient cluster extraction
Data Mining course projects
Data Mining course projects
Coordinated logistics with a truck and a drone
Calculating pairwise euclidean distance matrix for horizontally partitioned data in federated learning environment
Assignments of the Data Mining course COL761(2018-19) @ IIT Delhi
GUI version of https://github.com/guglielmosanchini/ClustViz
Data Mining Applied to Oil Well Using K-means and DBSCAN (A Research Paper Implementation along with OPTICS and PCA)
Iris dataset
All-in-1 notebook which applies different clustering (K-means, hierarchical, fuzzy, optics) and classification (AdaBoost, RandomForest, XGBoost, Custom) techniques for the best model.
An implementation of OPTICS Algorithm
Final project for Data Mining course : Using OPTICS on 2 datasets
MATLAB scripts for the paper "Deep learning and 3D-DESI imaging reveal the hidden metabolic heterogeneity of cancer"
Sklearn, K-means Clustering, Hierarchical Clustering, DBSCAN, Mean Shift Clustering, Gaussian Mixture Models (GMM), Spectral Clustering, Affinity Propagation, OPTICS (Ordering Points to Identify the Clustering Structure), Birch (Balanced Iterative Reducing and Clustering using Hierarchies), marketing_campaign
For this group project, I performed cluster analysis and classification using Python to predict one of three classes for water pumps; functional, functional but needs repair, and non-functions. I used clustering to find hidden data structures to exploit for fitting individual classification techniques with better results than using the entire dataset. Unfortunately, k-means clustering, DBSCAN, hierarchical clustering, nor OPTICS produced well-defined clusters. The entire dataset was therefore used for fitting classification algorithms. The two classification techniques I was responsible for were k-nearest neighbors and stacked generalization ensemble. For the latter, I combined the best models each group member developed. All the models had a hard time predicting the functional but need repair class. My best model was only able to achieve an accuracy of 76%.
Personal research project on examining different types of clustering algorithms, as well as investigate their impact when they are used in classification problem (cluster-based feature engineering)
Implementation of Density-based clustering algorithms for Geo-social data
Модуль 6. Навчання без вчителя. Кластерізація. KMeans. Principal Component Analysis
An Implementation of Data Mining Algorithms, namely K-Means, DBScan, OPTICS.