157 Open source projects that are alternatives of or similar to goscore

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

Machine Learning University: Decision Trees and Ensemble Methods

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

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

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

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

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

Machine Learning Lectures at the European Space Agency (ESA) in 2018

This is the implementation of Sparse Projection Oblique Randomer Forest

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python

Misc Statistics and Machine Learning codes in R

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…

Python code for common Machine Learning Algorithms

simple tutorial on Machine Learning with Scikitlearn

A python library for decision tree visualization and model interpretation.

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

Ruby Scoring API for PMML

Text Classification Algorithms: A Survey

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

A python library to build Model Trees with Linear Models at the leaves.

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

Machine learning for C# .Net

🍊 📊 💡 Orange: Interactive data analysis

A fast and easy to use decision tree learner in java

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

An end-to-end machine learning and data mining framework on Hadoop

several methods for text classification

Machine Learning algorithms coded from scratch

Seminar work "Decision Trees - An Introduction" with presentation, seminar paper, and Python implementation

InfiniteBoost: building infinite ensembles with gradient descent

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

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.

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

Python PMML scoring library

A set of tools to understand what is happening inside a Random Forest

A random forest

Machine Learning inference engine for Microcontrollers and Embedded devices

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

Machine Learning library written in Python and NumPy.

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

A collection of research papers on decision, classification and regression trees with implementations.

YouTube Like Count Predictions using Machine Learning

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

Hyperon - Motor Insurance Demo App. This is a sample application to demonstrate capabilities of Hyperon.io library (Java Business Rules Engine (BRE)/Java Pricing Engine). The application demonstrates responsive quotations for Car/Motor Insurance based on decision tables and Rhino functions (for math calculations). It shows different possible bus…

🌳 Stacked Gradient Boosting Machines

Heart Disease prediction using 5 algorithms

随机森林，Random Forest（RF）

Handwritten Digit Recognition using Machine Learning and Deep Learning

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…

ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

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

An umbrella project for multiple implementations of model serving

A New, Interactive Approach to Learning Data Science

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