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Name: OpenMind
Type: User
Name: OpenMind
Type: User
In this project, we have implemented different supervised learning algorithms and then compared their performances. The following algorithms were implemented: 1) libSvm 2) Multiclass KSVM 3) Random Forests 4) Deep Learning (CNN, MLP) 5) Naïve Bayes 6) AdaBoost This report includes description, implementation details, performance, and results of each mentioned algorithm on given datasets. It also includes the comparison of the accuracies of the aforementioned algorithms.
Deep Learning to Improve Breast Cancer Detection on Screening Mammography
I have done my individual project (dissertation) on ensemble methods. In which I first did the background study on different ensemble methods and then implemented Boosting, AdaBoost, Bagging and random forest techniques on underlying machine learning algorithms. I used boosting method to boost the performance of weak learner like decision stumps. Implemented bagging for decision trees (both regression and classification problems) and for KNN classifier. Used random forest for classification trees. I have implemented a special algorithm of boosting called “AdaBoost” on logistic regression algorithm using different threshold values. Then plotted the different graphs like an error rate as a function of boosting, bagging and random forest iterations. Compared results of bagging with boosting. Analysed the performance of classifier before applying ensemble methods and after applying ensemble methods. Used different model evaluation techniques like cross-validation, MSE, PRSS, ROC curves, confusion matrix, and out-of-bag error estimation to estimate the performance of ensemble techniques.
ERPLAB Toolbox is a free, open-source Matlab package for analyzing ERP data. It is tightly integrated with EEGLAB Toolbox, extending EEGLAB’s capabilities to provide robust, industrial-strength tools for ERP processing, visualization, and analysis. A graphical user interface makes it easy for beginners to learn, and Matlab scripting provides enormous power for intermediate and advanced users.
Lecture notes for estimation and detection theory
Lecture Notes in Mathematics
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Code and data for "The Geometry of Classifiers"
Exploring scalability issues in R using H2O package and image classification using Tensorflow
Extremely simple one-shot learning in Python
a R implementation of extreme learning machine
Segmentation vasculature in retinal image
Face verification experiment for lfw
Implementing Siamese networks with a contrastive loss for similarity learning
Extract and Visualize the Results of Multivariate Data Analyses
Multivariate imputation and matrix completion algorithms implemented in Python
A MNIST-like fashion product database. Benchmark :point_right:
FastAST - A fast primal-dual interior point method for line spectral estimation via atomic norm soft thresholding.
Author of All Files under this Folder: Xiaoming Huo
:book: [译] fast.ai 机器学习和深度学习中文笔记
The fastai book, published as Jupyter Notebooks
Fast Lane to Learning R!
A faster pytorch implementation of faster r-cnn
Faster R-CNN
Fastfit matlab toolbox
Matlab code for all variants of robust PCA and SPCP
Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.
An open-source framework for benchmarking of feature selection algorithms and cost functions.
Computer vision feature extraction toolbox for image classification
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.