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Name: Lihao
Type: User
Name: Lihao
Type: User
Config files for my GitHub profile.
Breast cancer diagnosis using multiple statistical/machine learning techniques: XGBoost, support vector machine, random forest, k-neighbours, and deep learning
Predicting the probability that a diagnosed breast cancer case is malignant or benign based on Wisconsin dataset
Supervised Learning Model to predict breast cancer
Classification of Breast Cancer diagnosis Using Support Vector Machines
Breast Cancer Diagnosis Using Machine Learning Random Forest and XGBoost Method
Breast cancer diagnosis using machine learning via the XGBoost Algorithm after visualizing the data set & exploring it.
This repository contains code and dataset for Cervical Cancer Prediction using XGBoost algorithm in Machine Learning
Come and join us, we need you!
Different approaches as (ANN,DecisionTree,Bayes and KNeighbors) to solve and predict with the best accuracy malignous cancers
Using a looped code to run Linear Regression, Lasso Regression, Ridge Regression, Elastic Net, KNN, SVM, XGBoost, Ada Boost, Random Forest, Gradient Boost and Neural Network. and KNN to predict cancer
We used different machine learning approaches to build models for detecting and visualizing important prognostic indicators of breast cancer survival rate. This repository contains R source codes for 5 steps which are, model evaluation, Random Forest further modelling, variable importance, decision tree and survival analysis. These can be a pipeline for researcher who are interested to conduct studies on survival prediction of any type of cancers using multi model data.
This project is all about a Machine Learning based Medical Test web app which makes predictions about various diseases using the concept of machine learning.
技术面试最后反问面试官的话
CNN-RNN中文文本分类,基于TensorFlow
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
This project creates an eXtreme Gradient Boosting (XGBoost) machine learning model to determine which genes best predict whether a patient will develop two cancer symptoms: Perineural Invasion (PNI) and Lymphovascular Invasion (LVI).
The house price was estimated based on the user's choices. Xgboost was used for training the model and Streamlit was used for deployment.
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.