xuesenyang Goto Github PK
Type: User
Company: Shenzhen University
Bio: You are all stardust.
Type: User
Company: Shenzhen University
Bio: You are all stardust.
Code of article 'A two-dimensional (2-D) learning framework for Particle Swarm based feature selection'
Implementation and Analysis of AI algorithms - Best First Search , Beam Search , A Star Search , Hill Climbing
One Boosted Regression Tree method in Prediction of Industrial Steam Volume after variable selection
Implementation of a competitive swarm optimizer (CSO) for feature selction
Implementation of curious-feature-selection
A noval feature selection method similar to pagerank method, and ultilized Bayesian optimization to search appropriate parameters
Some common financial risk control models
Implementation of feedforward neural network based on numpy
FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.
A graph clustering method with ant colony optimization for feature selection
In classification, Accuracy, Precision, Recall, F1, Confusion Matrix, ROC, AUC are the important Evaluation Indicator
An improved decision tree classifier, in which the feature ranking threshold is used to replace Gini coefficient or information gain rate, as a criterion for judging whether a feature can be used as a tree node.
using a single IsolationForest method to rank features
A framework for single/multi-objective optimization with metaheuristics
Layered sampling 10 fold cross validation+30runtimes+Multiple assessment
使用LSTM、GRU、BPNN进行时间序列预测。Using LSTM\GRU\BPNN for time series forecasting. (Pytorch Edition)
Machine Learning Decision Tree
机器学习练习
Applied generative adversarial networks (GANs) to do anomaly detection for time series data
A Factorization Machines for Multiple Classification Tasks.
Implementation of people counter using object detection with YOLO_v3 and object tracking
Python - 100天从新手到大师
A simple reinforcement learning for feature selection
Several simple feature extraction methods are PCA, LDA, SVD and LLE
Several Simple Regression Prediction Methods(including-SVR, LR, Lasso, ElasticNet, Gradient Boosting, Xgboost, lightGBM, Random Forest)
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.