Popular GitHub Repositories for Randomforest

Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification

A Unified Framework for Random Forest Prediction Error Estimation

Twitter US Airline数据集情感分析（sentiment Analysis），使用Bert Sentence encoding作为特征，实现了SVM、XGBoost、RandomForest（随机森林）若干分类器。

Lung Cancer Prediction using Machine Learning Algorithms

Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties

Fraud detection using lgb, catboost, rf, etc

Plot tree based machine learning models

Prediction of Customer Churn using Spark Mllib

Kaggle Competition: Backpack Price Prediction. Built ML models (Linear/Ridge Regression, XGBoost, etc.) with EDA, feature engineering, and MAE evaluation (best ~39.18). Includes notebooks for data preprocessing, model training, and insights. Great for learning regression techniques and Kaggle workflows

Create a bioactivity prediction model using molecular descriptors (PADEL) and supervised machine learning (ML).

This project is the application of machine learning algorithms to predict bioactivity of IC50 type molecules on SARS Coronavirus (Replicase polyprotein 1ab single-protein database).

MACHINE LEARNING / NLP / AMAZON SAGEMAKER: Plagiarism detector in 3 ML model versions (XGBoost, Random Forest & my implemementation) deployed on Amazon SageMaker.

This repository contains a Flask application for detecting phishing URLs using machine learning. It includes preprocessing, feature extraction, model training, and model deployment in a web application.

Random Forest Binary Classification is applying on sample data in PySpark on Jupyter Notebook

SVM, Logistic Regression, K-Nearest Neighbors Classifier, GaussianNB, Random Forest, XGBoost, DecisionTree Classifier, Ensembled Classifier, ExtraTrees Classifier, Voting Classifier

Forecasting stock prices of S&P500 using RandomForest and LSTM (Pytorch)

Differentiable relaxations of tree-based models.

AI 小项目代码、笔记

Nonlinear Regression Models

Classification of emotion on textual data using DecisionTree, RandomForest Classifier and LSTM based deep learning algorithm. This project also uses TF-IDF vectorizer and word embedding process to encode the textual data in numeric form.