105 Open source projects that are alternatives of or similar to Decision Tree Js

R package "missRanger" for fast imputation of missing values by random forests.

Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18

A Unified Framework for Random Forest Prediction Error Estimation

Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

A scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.

Machine Learning University: Decision Trees and Ensemble Methods

(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset

This repo contains regression and classification projects. Examples: development of predictive models for comments on social media websites; building classifiers to predict outcomes in sports competitions; churn analysis; prediction of clicks on online ads; analysis of the opioids crisis and an analysis of retail store expansion strategies using…

Online machine learning methods

Solution of the Titanic Kaggle competition

Predicting the winner of 2019 cricket world cup using random forest algorithm

Master's degree project: Development of a trading algorithm which uses supervised machine learning classification techniques to generate buy/sell signals

📈 Click-Through Rate Prediction using Logistic Regression and Tree Algorithms

Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand

Efficient Online Transfer Learning for 3D Object Detection in Autonomous Driving

Jupyter Notebooks and miscellaneous

A Random Survival Forest implementation for python inspired by Ishwaran et al. - Easily understandable, adaptable and extendable.

Random Forests for Density Estimation in Python

bitcoin prediction algorithms

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Ruby Scoring API for PMML

Using LSTM network for time series forecasting

A tool for visualizing the structure and performance of Random Forests 🌳

Statistical inference on machine learning or general non-parametric models

A document covering machine learning basics. 🤖📊

Go Scoring API for PMML

It's a github repo star predictor that tries to predict the stars of any github repository having greater than 100 stars.

A super-fast and scalable Random Forest library based on fast histogram decision tree algorithm and distributed bagging framework. It can be used for binary classification, multi-label classification, and regression tasks. This library provides both Python and command line interface to users.

In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).

Machine Learning algorithms coded from scratch

Receipt.ID is a multi-label, multi-class, hierarchical classification system implemented in a two layer feed forward network.

Scripts, tools and example data for mapping wetland ecosystems using data driven R statistical methods like Random Forests and open source GIS

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

ML-powered Loan-Marketer Customer Filtering Engine

Misc Statistics and Machine Learning codes in R

This is the official implementation for the paper 'AutoEncoder by Forest'

A random forest

Machine Learning library written in Python and NumPy.

Heart Disease prediction using 5 algorithms

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

Conformalized Quantile Regression

Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning

Building Decision Trees From Scratch In Python