bagging

There are 1 repository under bagging topic.

TorchEnsemble-Community / Ensemble-Pytorch
A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.
pytorch pytorch-tutorial ensemble-learning ensemble deeplearning neural-networks deep-learning gradient-boosting voting-classifier bagging
Language:Python 1066
vecxoz / vecstack
Python package for stacking (machine learning technique)
stacking stacked-generalization explain-stacking stacking-tutorial blending bagging ensembling ensemble ensemble-learning machine-learning
Language:Python 685
a-martyn / ISL-python
Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
machine-learning statistical-learning islr supervised-learning linear-regression logistic-regression random-forest boosting-algorithms bootstrap bagging pca lda
Language:Jupyter Notebook 293
mlr3pipelines
mlr-org / mlr3pipelines
Dataflow Programming for Machine Learning in R
mlr3 machine-learning pipelines preprocessing bagging stacking ensemble-learning r dataflow-programming r-package data-science
Language:R 134
damianhorna / multi-imbalance
Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/
multi-class-imbalance class-imbalance machine-learning preprocessing ensembles smote resampling decomposition decision-trees bagging python python-package undersampling oversampling balancing
Language:Python 75
serengil / decision-trees-for-ml
Building Decision Trees From Scratch In Python
decision-tree gradient-boosting gradient-boosting-machine boosting bagging id3 c45 cart regression-trees lightgbm xgboost random-forest machine-learning gbm adaboost
Language:Jupyter Notebook 62
sharmaroshan / Drugs-Recommendation-using-Reviews
Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.
recommendation-system data-visualization data-analysis data-mining data-cleaning feature-engineering feature-selection machine-learning deep-learning hybrid-model boosting-algorithms bagging
Language:Jupyter Notebook 60
nursnaaz / 25DaysInMachineLearning
I will update this repository to learn Machine learning with python with statistics content and materials
python machine-learning machine-learning-algorithms machinelearning machinelearning-python statistics data-science modelling python3 data-preprocessing practise descriptive-statistics bias linear-regression decision-tree numpy covariance logistic-regression random-forest bagging
Language:Jupyter Notebook 58
Machine_Learning
SudhakarKuma / Machine_Learning
A repository of resources for understanding the concepts of machine learning/deep learning.
machine-learning imbalanced-data seaborn-plots smote f1-score supervised-machine-learning unsupervised-machine-learning clustering preprocessing critical-concepts dimensionality-reduction knn-classification bagging boosting datacamp-machine-learning summer-school iiith datacamp-projects
Language:Jupyter Notebook 36
forestry-labs / Rforestry
random-forests trees interpretability bagging boosting causal-inference machine-learning monotonic-constraints r r-package random-forest
Language:C++ 34
AaronWard / PU-learning-example
An example repo for how PU Bagging and TSA works.
positive-unlabeled-learning pulearning bagging bagging-trees machine-learning labelling weakly-supervised-learning semi-supervised-learning random-forest ensemble-machine-learning ensemble unreliable-labels
Language:Python 33
anishsingh20 / Statistical-Learning-using-R
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.
datascience statistical-learning r data-analysis depth-interpretation machine-learning-algorithms predictive-modeling polynomial-regression k-nn boosting bagging generalized-additive-models discriminant-anlaysis decision-trees svm-classifier logistic-regression supervised-machine-learning regularization clustering-algorithm
Language:R 31
sayaliwangane / INTELLIGENT-CAREER-GUIDANCE-SYSTEM
Web application for engineering students to predict appropriate job roles using Machine learning and other guidance material like job descriptions, links to courses, etc.
machine-learning knn knn-classification knn-algorithm webapp php python flask-application pickle css bagging numpy pandas sklearn
Language:PHP 24
spark-ensemble
pierrenodet / spark-ensemble
Ensemble Learning for Apache Spark 🌲
bagging boosting ensemble-learning gbm machine-learning scala spark spark-ml stacking
Language:Scala 21
frankkramer-lab / ensmic
An analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks
deep-learning ensemble-learning study image-classification augmenting bagging stacking
Language:Python 17
ysh329 / awesome-deep-learning-finetune-experience
This repository not only contains experience about parameter finetune, but also other in-practice experience such as model ensemble (boosting, bagging and stacking) in Kaggle or other competitions.
deep-learning finetune experience kaggle-competition practice fine-tuning-cnns fine-tuning ensemble-learning bagging boosting stacking
16
wslc1314 / TextSentimentClassification
TextSentimentClassification, using tensorflow.
textclassification textcnn textrnn crnn rcnn hierarchical-attention-networks bagging stacking tensorflow
Language:Python 15
rafaelvareto / HPLS-HFCN-openset
Paper: Towards Open-Set Face Recognition using Hashing Functions (IJCB'17)
face-recognition machine-learning bagging pls svm open-set hash-functions paper
Language:Python 13
LaxmiChaudhary / Modeling-of-strength-of-high-performance-concrete-using-Machine-Learning
feature-selection random-forest exploratory-data-analysis feature-engineering decisiontree gradient-boosting adaboost bagging knn-regression support-vector-regression ensemble-machine-learning kfold-cross-validation bootstrap supervised-learning supervised-machine-learning regression-algorithms
Language:Jupyter Notebook 12
zpysky1125 / Ensembling
Sklearn implement of multiple ensemble learning methods, including bagging, adaboost, iterative bagging and multiboosting
ensemble-learning boosting-algorithms bagging
Language:Python 12
sun1638650145 / classicML
简单易用的经典机器学习框架
machine-learning python framework decision-tree support-vector-machine logistic-regression linear-discriminant-analysis naive-bayes-classifier eigen pybind11 cpp17 adaboost ensemble-learning neural-network bagging cluster
Language:Python 10
vikasgupta1812 / Machine_Learning
Predictive Machine Learning projects
machine-learning adaboost bagging decision-trees random-forest
Language:HTML 10
UnixJunkie / orf
OCaml Random Forests
classification regression machine-learning statistical-modeling ocaml-library random-forests out-of-bag bagging bootstrap-aggregation
Language:OCaml 8
anubhavshrimal / Quick-Draw
Implementation of Google Quick Draw doodle recognition game in PyTorch and comparing other classifiers and features.
quick-draw pytorch computer-vision classification-algorithims xgboost naive-bayes-classifier svm-classifier bagging knn-classification random-forest
Language:Jupyter Notebook 7
gulabpatel / Machine-Learning
Regression, Classification, Clustering, Dimension-reduction, Anomaly detection
regression adaboost bagging boosting catboost classification clustering gradient-boosting lightgbm stacking xgboost crossvalidation gmm gmm-clustering pca dbscan hdbscan umap dimentionality-reduction folium
Language:Jupyter Notebook 7
Gurudev333 / Loan_Prediction_by_ensemble_machine_learning_techniques
Used ensemble methods such as boosting, voting, Bagging
boosting-algorithms ensemble-classifier bagging voting machine-learning random-forest
Language:Jupyter Notebook 6
sahirnoorali / poker-hand-analysis
Analysis and Prediction of Poker Hand Strength
machine-learning deep-learning scikit-learn poker-hands python svm-classifier adaboost random-forest bagging decision-tree-classifier knn-classifier naive-bayes-classifier multi-layer-perceptron prediction analysis
Language:Python 6
sergii1989 / FastMLFramework
FastML Framework is a python library that allows to build effective Machine Learning solutions using luigi pipelines.
machine-learning pipeline luigi feature-engineering feature-selection hyperparameter-optimization stacking blending bagging auto-ml classification regression cross-validation lightgbm xgboost
Language:Python 6
sharmaroshan / Don-t-Overfit
It is from Kaggle Competitions where the training dataset is very small and the testing dataset is very large and we have to avoid or reduce overfiting by looking for best possible ways to overcome the most popular problem faced in field of predictive analytics.
overfitting linear-models linear-regression lasso pystan stacking bagging shuffle-split machine-learning competitive-programming-contests logistic-regression
Language:Jupyter Notebook 6
anubhavshrimal / SML-Malaria-Detection
Compare Naive Bayes, SVM, XGBoost, Bagging, AdaBoost, K-Nearest Neighbors, Random Forests for classification of Malaria Cells
statistical-machine-learning machine-learning malaria-detection classification-algorithims xgboost naive-bayes-classifier svm-classifier bagging boosting-algorithms knn-classification random-forest
Language:Jupyter Notebook 5
Python-Chilla-2.0
ArslanKAS / Python-Chilla-2.0
All the content that I learned through two Courses. One is called "Python Chilla" and the second one is called "100 Days of Machine Learning"
bagging boosting-algorithms data datascience ensemble-learning machine-learning-algorithms numpy pandas scikit-learn voting
Language:Jupyter Notebook 5
arunvignesh15 / Machine-Learning
Learn and Explore
machine-learning classification regression random-forest xgboost tpot gridsearchcv bagging cross-validation imbalanced-learning smote svm-classifier knn-classification
Language:Jupyter Notebook 5
Aviator10 / Analysis-and-prediction-of-online-shoppers-purchasing-intention-using-various-algorithms-CAPSTONE
Build a predictive machine learning model that could categorize users as either, revenue generating, and non-revenue generating based on their behavior while navigating a website. In order to predict the purchasing intention of the visitor, aggregated page view data kept track during the visit along with some session is used and user information as input to machine learning algorithms. Oversampling/Undersampling and feature selection techniques are applied to improve the success rates and scalability of the models.
machine-learning xgboost hyperparameter-tuning ensemble-learning bagging boosting stacking blending tableau python logistic-regression knn svm naive-bayes voting random-forest votingclassifier decision-tree
Language:Jupyter Notebook 5
Chandrakant817 / Machine-Learning-Handwritte-Notes
Entire Machine Learning Hand Written Notes
bagging boosting clustering dbscan decision-trees ensemble-learning kmeans-clustering knn linear-regression logistic-regression machine-learning machine-learning-algorithms maths pca random-forest stacking time-series
5
codekhal / Inshorts-NLP
Analysed syntax and Semantics of Corpus of Text Documents Retrieved from Web Scraping of News articles from Inshorts and followed the Standard NLP Workflow of the CRISP-DM model.
nlp tokenizer stemming lemmatization bagging postagging python3 shallow-parsing data-mining webscraping dependancy-parsing named-entity-recognition sentiment-analysis inshorts semantics inshorts-nlp
Language:Jupyter Notebook 5
ravitejaCR7 / Machine-Learning
numpy python3 decision-trees linear-regression boosting bagging knearest-neighbor-algorithm gradient-descent stochastic-gradient-descent svm-model kmeans-clustering spectral-clustering svm kmeans-clustering-algorithm matplotlib scikit-learn pandas numpy-library naive-bayes-classifier
Language:Python 5

bagging

TorchEnsemble-Community / Ensemble-Pytorch

vecxoz / vecstack

a-martyn / ISL-python

mlr-org / mlr3pipelines

damianhorna / multi-imbalance

serengil / decision-trees-for-ml

sharmaroshan / Drugs-Recommendation-using-Reviews

nursnaaz / 25DaysInMachineLearning

SudhakarKuma / Machine_Learning

forestry-labs / Rforestry

AaronWard / PU-learning-example

anishsingh20 / Statistical-Learning-using-R

sayaliwangane / INTELLIGENT-CAREER-GUIDANCE-SYSTEM

pierrenodet / spark-ensemble

frankkramer-lab / ensmic

ysh329 / awesome-deep-learning-finetune-experience

wslc1314 / TextSentimentClassification

rafaelvareto / HPLS-HFCN-openset

LaxmiChaudhary / Modeling-of-strength-of-high-performance-concrete-using-Machine-Learning

zpysky1125 / Ensembling

sun1638650145 / classicML

vikasgupta1812 / Machine_Learning

UnixJunkie / orf

anubhavshrimal / Quick-Draw

gulabpatel / Machine-Learning

Gurudev333 / Loan_Prediction_by_ensemble_machine_learning_techniques

sahirnoorali / poker-hand-analysis

sergii1989 / FastMLFramework

sharmaroshan / Don-t-Overfit

anubhavshrimal / SML-Malaria-Detection

ArslanKAS / Python-Chilla-2.0

arunvignesh15 / Machine-Learning

Aviator10 / Analysis-and-prediction-of-online-shoppers-purchasing-intention-using-various-algorithms-CAPSTONE

Chandrakant817 / Machine-Learning-Handwritte-Notes

codekhal / Inshorts-NLP

ravitejaCR7 / Machine-Learning