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61 search results found

Orange3 ⭐ 4,469

🍊 📊 💡 Orange: Interactive data analysis

Machine Learning With Python ⭐ 2,980

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

Mljar Supervised ⭐ 2,867

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Dtreeviz ⭐ 2,720

A python library for decision tree visualization and model interpretation.

Awesome Decision Tree Papers ⭐ 2,266

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

Text_classification ⭐ 1,621

Text Classification Algorithms: A Survey

Awesome Gradient Boosting Papers ⭐ 930

A curated list of gradient boosting research papers with implementations.

Ai_all_resources ⭐ 647

A curated list of Best Artificial Intelligence Resources

Decision Forests ⭐ 635

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

Chefboost ⭐ 428

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

Yggdrasil Decision Forests ⭐ 403

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

Sharplearning ⭐ 372

Machine learning for C# .Net

Machine Learning Is All You Need ⭐ 337

🔥🌟《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!

Decisiontree.jl ⭐ 326

Julia implementation of Decision Tree (CART) and Random Forest algorithms

2018 Machinelearning Lectures Esa ⭐ 324

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

Linear Tree ⭐ 253

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

Intrusion Detection System Using Machine Learning ⭐ 248

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

Decision Tree Js ⭐ 237

Small JavaScript implementation of ID3 Decision tree

Python_decision_tree_and_random_forest ⭐ 184

I've demonstrated the working of the decision tree-based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample. All the steps have been explained in detail with graphics for better understanding.

Aws Machine Learning University Dte ⭐ 177

Machine Learning University: Decision Trees and Ensemble Methods

Machine_learning_algorithms_from_scratch ⭐ 164

This repository explores the variety of techniques and algorithms commonly used in machine learning and the implementation in MATLAB and PYTHON.

Machine Learning In R ⭐ 144

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

This is the implementation of Sparse Projection Oblique Randomer Forest

Stock Return Prediction Using Knn Svm Guassian Process Adaboost Tree Regression And Qda ⭐ 85

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

Network Intrusion Detection ⭐ 85

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

Betaml.jl ⭐ 83

Beta Machine Learning Toolkit

Machine Learning Models ⭐ 81

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

Ruby Scoring API for PMML

Top 10 Machine Learning Methods With R ⭐ 61

Includes top ten must know machine learning methods with R.

Click Through Rate Prediction ⭐ 60

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

Predicting_real_estate_prices_using_scikit Learn ⭐ 59

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)

Scikit Tree ⭐ 51

Scikit-learn compatible decision trees beyond those offered in scikit-learn

25daysinmachinelearning ⭐ 48

I will update this repository to learn Machine learning with python with statistics content and materials

Go Scoring API for PMML

Proglearn ⭐ 33

NeuroData's package for exploring and using progressive learning algorithms

Broomstick ⭐ 29

🌲 broom helpers for decision tree methods (rpart, randomForest, and more!) 🌲

Breast Cancer Scikitlearn ⭐ 27

simple tutorial on Machine Learning with Scikitlearn

Decision Trees For Ml ⭐ 27

Building Decision Trees From Scratch In Python

Machine Learning Models ⭐ 26

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

Incrementaltrees ⭐ 26

Adds partial fit method to sklearn's forest estimators to allow incremental training without being limited to a linear model. Works with Dask-ml's Incremental.

R Stats Machine Learning ⭐ 25

Misc Statistics and Machine Learning codes in R

Sentimentanalysis ⭐ 21

(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

Fortlearner ⭐ 21

Machine Learning Algorithms in Fortran

Machine Learning Techniques ⭐ 20

Repository containing introduction to the main methods and models used in machine learning problems of regression, classification and clustering.

Fudanuniversity Datamining ⭐ 18

2020 Spring Fudan University Data Mining Course HW by prof. Zhu Xuening. 复旦大学大数据学院2020年春季课程-数据挖掘（DATA620007）包含数据挖掘算法模型：Line Regression Model、Logistic Regression Model、Linear Discriminant Analysis、K-Nearest Neighbour、Naive Bayes Classifier、Decision Tree Model、AdaBoost、Gradient Boosting Decision Tree(GBDT)、XGBoost、Random Forest Model、Support Vector Machine、Principal Component Analysis(PCA)

Rulecovering ⭐ 17

Rule covering for interpretation and boosting

PyXAI (Python eXplainable AI) is a Python library (version 3.6 or later) allowing to bring formal explanations suited to (regression or classification) tree-based ML models (Decision Trees, Random Forests, Boosted Trees, ...).

Amazon Fine Food Review ⭐ 16

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 tool for visualizing the structure and performance of Random Forests 🌳

Supervised Machine Learning ⭐ 15

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 Lasso and Ridge regressions.

Aqi Delhi ⭐ 15

Predicting air pollution level in a specific city

Machine Learning Using Python ⭐ 15

Regression, Classification and Clustering

Predicting Baseball Statistics ⭐ 14

Predicting Baseball Statistics: Classification and Regression Applications in Python Using scikit-learn

Ml Algorithms From Scratch ⭐ 14

Here we have fully implemented a number of algorithms related to machine learning

Adaptiverandomforest ⭐ 14

Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04

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

Recursive Partitioning for Structural Equation Models

Df Dn Paper ⭐ 12

Conceptual & empirical comparisons between decision forests & deep networks

Email Spam Detection ⭐ 11

This project focuses on detecting Persian spam emails using machine learning algorithms. The goal is to develop an effective spam detection system using various word embedding techniques and classification algorithms. The project utilizes three word embedding algorithms: TF-IDF, Frequency of Words, and Bag of Words. Additionally, six classification

Mobile Price Prediction Classification Analysis ⭐ 10

Supervised Machine Learning Analysis Using Classification Models

Sentimentanalysis Python Demo ⭐ 10

Submission of an in-class NLP sentiment analysis competition held at Microsoft AI Singapore group. This submission entry explores the performance of both lexicon & machine-learning based models

Generic decision trees for rust

Nhanes R Programming ⭐ 9

This repository should help people that would like to code in R and work with the National Health and Nutrition Examination Survey (NHANES). Some topics corved are SQL , logistic regression.... etc

Disease Prediction Using Machine Learning ⭐ 9

Implementation of various machine learning algorithms to predict the disease from symptoms.

Sparkitecture ⭐ 9

A collection of “cookbook-style” scripts for simplifying data engineering and machine learning in Apache Spark.

Randomforests ⭐ 8

C++ implementation of random forests classification, regression, proximity and variable importance.

Machinelearning_exercises_python_scikit Learn ⭐ 8

Python＆機械学習ライブラリ scikit-learn の使い方の練習コード集。機械学習の理論解説付き

Network Traffic Classification ⭐ 8

Randomforests ⭐ 8

Random Forest Library In Python Compatible with Scikit-Learn

Bike Shairing Demand Prediction ⭐ 8

Supervised Machine Learning (Regression)

Data Science ⭐ 7

EDA and Machine Learning Models in R and Python (Regression, Classification, Clustering, SVM, Decision Tree, Random Forest, Time-Series Analysis, Recommender System, XGBoost)

Machine Learning Rare Event Classification ⭐ 7

With unbalanced outcome distribution, which ML classifier performs better? Any tradeoff?

Cpp Examples Ml ⭐ 7

Legacy OpenCV Machine Learning Examples (2.4.x, C++)

Artificial Intelligence Course Projects S2023 ⭐ 7

AI course projects for problems like searching such as BFS, IDS and A*, genetic algorithms, Minimax tree, Naive bayes for classification, Machine Learning algorithms for anticipating price of houses and a Neural Networks by different approaches(from scratch, pytorch, keras)

Machinelearningalgos ⭐ 7

Personal reimplementation of some ML algorithms for learning purposes

Cic Ids 2018 Intrusion Detection Classification ⭐ 6

Baseline experiments on training a Decision Tree Classifier and a Random Forest Classifier using Grid Search with Cross Validation on the CIC IDS 2018 dataset for training Machine Learning network intrusion detection classifier models.

Creditanalytics Loan Prediction ⭐ 6

A predictive model that uses several machine learning algorithms to predict the eligibility of loan applicants based on several factors

Woodpecker ⭐ 6

A python library used for tree structure interpretation.

Plot tree based machine learning models

Gender Voice Recognition_machine Learning ⭐ 6

Supervised Machine Learning Classification Algorithms using Python and R (Logistic Regression, Decision Tree, Random Forest, SVM)

Onestep Electron Content ⭐ 6

Content for onestep-electron.github.io

Machine Learning In Python ⭐ 5

My learnings on different algorithms of Machine Learning with Python .

Randomforestpruning Ismm 2017 ⭐ 5

Cost-complexity pruning of random forests

Full-featured Decision Trees and Random Forests learner.

Machine Learning Bootcamp ⭐ 5

A beginner friendly ML course designed by us at Hermes AI Center for everyone with no prior knowledge in computer science concepts.

Text Classification Ml ⭐ 5

Application of various text classification algorithms on multiple datasets.

Machine Learning ⭐ 5

A comprehensive comparison of decision tree and random forest for cancer classification.

Data Analysis On Hospital Readmission Data ⭐ 5

Analysis on hospital readmission data for diabetic patients using R and Tableau

Mobile Phones Price Prediction ⭐ 5

A set of different models, that can be used to predict price range of a mobile phone.

Depthhead ⭐ 5

Head pose estimation using depth data and a hough forest

Syndrome_prediction ⭐ 5

Syndrome Prediction Helps to predict the disease through analysing group of symptoms

Deep Neural Decision Forests ⭐ 5

A model combining Deep Neural Networks and (Stochastic) Random Forests.

Pylearning ⭐ 5

Simple high-level machine-learning library in Python

Ml_from_scratch ⭐ 5

ML Algorithms from Scratch

q statistical learning

Machine Learning Practice ⭐ 5

Repository containing introduction to scikit-learn to provide hands-on problem solving experience for all the methods and models learnt in MLT.

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