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Name: Yuning Lei
Type: User
Name: Yuning Lei
Type: User
This clustering process iteratively applies K-Means on subdivided data, refining clusters through outlier identification and Mahalanobis Distance measurements, culminating in an optimized segmentation of the dataset into distinct, statistically significant clusters.
This project explores interpretable machine learning models using Decision Trees for classification and LASSO, Ridge Regression, PCR, and Boosting techniques for regression, applied to Acute Inflammations and Communities and Crime datasets, focusing on model interpretability, feature analysis, and optimization.
This project utilizes the Spark Framework and GraphFrames library to implement the Girvan-Newman algorithm, detecting communities in social networks by analyzing user connections based on common business reviews and optimizing modularity through iterative edge removal.
This project explores the potential relationship between continental eating habits and diabetes mortality rates worldwide. Utilizing data scraped from three web sources, I conducted a detailed analysis that includes visualizing dietary patterns, correlating average caloric intake by continent, and examining diabetes-related death statistics.
This project developed and optimized a hybrid recommendation system that processes over 450,000 training data points and 142,000 validation data points. The system combines user ratings, merchant details, and user reviews to predict users' ratings for restaurants they have not visited.
The assignment comprises two main tasks: implementing LSH to identify similar businesses based on user ratings and developing various collaborative filtering recommendation systems to predict user ratings for businesses.
This dashboard is a tool that shows the prevalence and patterns of mental health illness as well as the related health care service based on county-level data among the United States. It also compares the public interests in mental health with the data from Google Search Trends.
This project applies SVM classifiers and K-Means clustering to the Anuran Calls (MFCCs) dataset for multi-class, multi-label classification, evaluating techniques like binary relevance, SMOTE, and Classifier Chains to optimize label prediction accuracy.
This project creates a real-time review system for LA Veranda Hotel, using Flask and WebSocket to mimic Firebase. It enables easy data manipulation through RESTful APIs and real-time review submissions and monitoring, aiming to improve guest experiences by facilitating instant feedback and management response.
This project conducts a thorough analysis of the Combined Cycle Power Plant dataset through linear regression, polynomial modeling, and KNN regression, exploring variable interactions and nonlinear associations to predict electrical energy output accurately.
This homework leverages SMOTE for addressing class imbalance in a high-dimensional dataset, employing tree-based methods like random forest and XGBoost with model trees to enhance classification performance on the APS Failure at Scania Trucks dataset.
This assignment focuses on implementing the SON Algorithm using the Spark Framework to identify frequent itemsets within large datasets.
This study evaluates Supervised, Semi-Supervised, and Unsupervised Learning methods on the Breast Cancer Wisconsin and Banknote Authentication datasets, comparing their effectiveness through Monte-Carlo Simulation across multiple performance metrics.
This project utilizes transfer learning with pre-trained models EfficientNetB0 and VGG16 in Keras to accurately classify 20 bird species from images, achieving up to 79.53% accuracy with techniques like image augmentation and fine-tuning the last layer.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.