Machine-Learning-ModelsIn This repository I made some simple to complex methods in machine learning. Here I try to build template style code.
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scorubyRuby Scoring API for PMML
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receiptdIDReceipt.ID is a multi-label, multi-class, hierarchical classification system implemented in a two layer feed forward network.
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ShifuAn end-to-end machine learning and data mining framework on Hadoop
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random-survival-forestA Random Survival Forest implementation for python inspired by Ishwaran et al. - Easily understandable, adaptable and extendable.
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loloA random forest
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missComparemissCompare R package - intuitive missing data imputation framework
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Shapley regressionsStatistical inference on machine learning or general non-parametric models
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cheapmlMachine Learning algorithms coded from scratch
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ChefboostA 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
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efficient online learningEfficient Online Transfer Learning for 3D Object Detection in Autonomous Driving
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scibloxsciblox - Easier Data Science and Machine Learning
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supervised-machine-learningThis 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…
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arboretoA scalable python-based framework for gene regulatory network inference using tree-based ensemble regressors.
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ALRAImputation method for scRNA-seq based on low-rank approximation
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Orange3🍊 📊 💡 Orange: Interactive data analysis
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ICC-2019-WC-predictionPredicting the winner of 2019 cricket world cup using random forest algorithm
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InfiniteboostInfiniteBoost: building infinite ensembles with gradient descent
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goscoreGo Scoring API for PMML
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dlime experimentsIn 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).
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RandomforestexplainerA set of tools to understand what is happening inside a Random Forest
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HIBAGR package – HLA Genotype Imputation with Attribute Bagging (development version only)
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SentimentAnalysis(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
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wetlandmapRScripts, tools and example data for mapping wetland ecosystems using data driven R statistical methods like Random Forests and open source GIS
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SSIM Seq2SeqSSIM - A Deep Learning Approach for Recovering Missing Time Series Sensor Data
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yggdrasil-decision-forestsA collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
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Loan-WebML-powered Loan-Marketer Customer Filtering Engine
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eForestThis is the official implementation for the paper 'AutoEncoder by Forest'
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onelearnOnline machine learning methods
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pykitmlMachine Learning library written in Python and NumPy.
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handson-ml도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.
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Trajectory-Analysis-and-Classification-in-Python-Pandas-and-Scikit-LearnFormed 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…
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forestErrorA Unified Framework for Random Forest Prediction Error Estimation
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cqrConformalized Quantile Regression
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BetaML.jlBeta Machine Learning Toolkit
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AIML-ProjectsProjects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
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Decision Tree JsSmall JavaScript implementation of ID3 Decision tree
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rfvisA tool for visualizing the structure and performance of Random Forests 🌳
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QuickmlA fast and easy to use decision tree learner in java
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TotalLeastSquares.jlSolve many kinds of least-squares and matrix-recovery problems
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Tensorflow Ml Nlp텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)
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Machine learning trading algorithmMaster's degree project: Development of a trading algorithm which uses supervised machine learning classification techniques to generate buy/sell signals
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Github-Stars-PredictorIt's a github repo star predictor that tries to predict the stars of any github repository having greater than 100 stars.
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MLDay18Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18
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Amazon-Fine-Food-ReviewMachine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review
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xforestA 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.
Stars: ✭ 20 (-52.38%)