ensemble-machine-learning

There are 13 repositories under ensemble-machine-learning topic.

h1st-ai / h1st
Power Tools for AI Engineers With Deadlines
automl autonomous-vehicles avionics cold-start collaboration cybersecurity data-science datascience-environment energy-optimization ensemble-machine-learning explainability hacktoberfest home-automation human-in-the-loop industrial-iot predictive-maintenance time-series trustworthy-datascience
Language:Jupyter Notebook 799
sharmapratik88 / AIML-Projects
Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
catboost computer-vision data-science data-visualization datascienceproject decision-tree-classifier ensemble-machine-learning gradient-boosting-classifier knearest-neighbor-algorithm logistic-regression machine-learning machinelearningprojects nlp oversampling random-forest recommendation-system statistics supervised-machine-learning support-vector-machines unsupervised-machine-learning
Language:Jupyter Notebook 142
nikitaprasad21 / ML-Cheat-Codes
Machine Learning Cheatsheet 2024
adaboost-algorithm decision-trees ensemble-machine-learning linear-regression logistic-regression python random-forest tensors xgboost
Language:Jupyter Notebook 125
mesa
ZhiningLiu1998 / mesa
[NeurIPS’20] ⚖️ Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题
imbalanced-learning imbalanced-data meta-learning-algorithms meta-sampler ensemble ensemble-model ensemble-machine-learning mesa meta-training class-imbalance imbalance-classification imbalanced-learn
Language:Jupyter Notebook 105
FilippoMB / Ensemble-Conformalized-Quantile-Regression
Valid and adaptive prediction intervals for probabilistic time series forecasting
probabilistic-forecasting time-series-forecasting time-series-prediction uncertainty-quantification frequentist-statistics frequentistic-confidence-intervals recurrent-neural-networks quantile-regression conformal-prediction random-forest prediction-intervals ensemble-machine-learning
Language:Jupyter Notebook 87
desh2608 / dover-lap
Python package for combining diarization system outputs.
diarization dover-lap ensemble-machine-learning
Language:Python 80
gkunapuli / ensemble-methods-notebooks
A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)
ensemble-learning ensemble-machine-learning jupyter-notebook machine-learning python scikit-learn
Language:Jupyter Notebook 75
dkanungo / Probabilistic-ML-for-finance-and-investing
Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python
finance investing probabilistic-programming trading uncertainty-quantification markov-chain-monte-carlo npv-analysis project-management aleatoric-uncertainty epistemic-uncertainty epistemology ontological-information ensemble-machine-learning generative-ai probabilistic-models capm maximum-likelihood-estimation portfolio-theory hamiltonian-monte-carlo monte-carlo-simulation
Language:Jupyter Notebook 74
louisowen6 / SENN
Code implementation of "SENN: Stock Ensemble-based Neural Network for Stock Market Prediction using Historical Stock Data and Sentiment Analysis"
stock-market-prediction neural-network ensemble-machine-learning mlp lstm cnn nlp stocktwits sentiment-analysis
Language:Jupyter Notebook 71
FernandoLpz / Stacking-Blending-Voting-Ensembles
This repository contains an example of each of the Ensemble Learning methods: Stacking, Blending, and Voting. The examples for Stacking and Blending were made from scratch, the example for Voting was using the scikit-learn utility.
ensemble-learning ensemble-machine-learning ensemble-classifier ensemble-model stacking stacking-ensemble blending voting machine-learning
Language:Python 52
alicex2020 / Deep-Learning-Lie-Detection
Use machine learning models to detect lies based solely on acoustic speech information
acoustic-features deep-learning ensemble-classifier ensemble-learning ensemble-machine-learning ensemble-model lie-detector machine-learning mfcc mfcc-analysis pitch-tracking support-vector-machines
Language:Jupyter Notebook 51
Dan-Boat / PyESD
Python Package for Empirical Statistical Downscaling. pyESD is under active development and all colaborators are welcomed. The purpose of the package is to downscale any climate variables e.g. precipitation and temperature using predictors from reanalysis datasets (eg. ERA5) to point scale. pyESD adopts many ML and AL as the transfer function.
machine-learning tensorflow2 sckit-learn precipitation downscaling ensemble-machine-learning deep-learning
Language:Python 48
jon-chun / sentimentarcs_notebooks
SentimentArcs: a large ensemble of dozens of sentiment analysis models to analyze emotion in text over time
affective ensemble ensemble-machine-learning feature-extraction machine-learning natural-language-processing nlp peak-detection sentiment sentiment-analysis time-series time-series-analysis transformers narrative finance narrative-extraction narrative-visualization social-media story storytelling
Language:Jupyter Notebook 39
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 32
ashishpatel26 / Most-used-ML-Packages
Here my amazing tutorial collection contain amazing notebook must read. It's contain pytorch, Advance pandas, Ensemble learning, Tensorflow, Genetic Algorithms, Dask, Word Embedding
pytorch pytorch-tutorial tensorflow tensorflow-tutorials pandas pandas-tutorial ensemble-learning ensemble-machine-learning word-embeddings nlp-machine-learning
Language:Jupyter Notebook 28
tonyleidong / OptimalFlow
OptimalFlow is an omni-ensemble and scalable automated machine learning Python toolkit, which uses Pipeline Cluster Traversal Experiments(PCTE) and Selection-based Feature Preprocessor with Ensemble Encoding(SPEE), to help data scientists build optimal models, and automate supervised learning workflow with simpler coding.
automl automated-machine-learning ensemble-machine-learning ensemble-encoder automated-feature-preprocessor
Language:HTML 27
nsl_kdd_classification
PradeepThapa / nsl_kdd_classification
Cyber-attack classification in the network traffic database using NSL-KDD dataset
nsl-kdd classification-algorithm catboost-model cyber-attacks-analytics kdd99 ensemble-machine-learning cyber-attack-classification classification-algorithms kdd-dataset network-traffic-database machine-learning-algorithms attack u2r r2l
Language:Python 23
action-ai-institute / MABEL-dataset
MABEL: Malware Analysis Benchmark for Artificial Intelligence and Machine Learning
artificial-intelligence deep-learning ensemble-learning ensemble-machine-learning machine-learning malware-analysis national-science-foundation natural-language-processing nlp python reverse-engineering software-reverse-engineering threat-intelligence
17
Haoning724 / obbstacking
Repo for the OBBStacking: An Ensemble Method for Remote Sensing Object Detection
deep-learning ensemble-machine-learning machine-learning object-detection oriented-bounding-box remote-sensing
Language:Python 17
Anello92 / Machine_Learning_Python
Top Machine Learning Algorithms Detailed in Python and Preprocessing for Machine Learning
machine-learning python preprocessing knn regression classification naive-bayes algorithm tree random-forest ensemble-machine-learning bagging-ensemble adaboost extremely-randomized-trees
Language:Jupyter Notebook 15
yashksaini-coder / Mohs-hardness-ensemble-prediction
Mohs Hardness Prediction Project | Ensemble Models with Neural Networks, LGBM, CAT, XGB using a Voting Mechanism. 🚀💎
catboost catboostregressor ensemble-learning ensemble-machine-learning ensemble-model lgbm lgbmregressor prediction prediction-model predictive-modeling supervised-learning catboost-mo
Language:Jupyter Notebook 15
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 13
fischlerben / Machine-Learning-Credit-Risk
Machine-Learning project that uses a variety of credit-related risk factors to predict a potential client's credit risk. Machine Learning models include Logistic Regression, Balanced Random Forest and EasyEnsemble, and a variety of re-sampling techniques are used (Oversampling/SMOTE, Undersampling/Cluster Centroids, and SMOTEENN) to re-sample the data. Evaluation metrics like the accuracy score, classification report and confusion matrix are generated to compare models and determine which suits this particular set of data best.
python pandas modeling logistic-regression random-forest ensemble-machine-learning accuracy-score confusion-matrix classification-report resampling smote cluster-centroids smoteenn
Language:Jupyter Notebook 11
pm390 / recsys2022
Code repo of solution of 11th place in Recsys Challenge 2022
recommender-systems solutions content-based-filtering deep-recsys item-collaborative-filtering lightgbm-models user-collaborative-filtering lgbmranker ensemble-machine-learning ranking re-ranking lambdarank
Language:Jupyter Notebook 11
IPVS-AS / pusion
Pusion (Python Universal Fusion) is a generic and flexible framework written in Python for combining multiple classifier’s decision outcomes.
auto-fusion autofusion decision-fusion ensemble-classifier ensemble-machine-learning fault-diagnosis hybrid-analytics
Language:Python 10
aayush1036 / housing-rent-prediction
End to End Machine Learning Project along with deployment.
machine-learning python data-science sklearn matplotlib-pyplot xgboost-regression random-forest numpy sql aws-rds-mysql flask python3 data-analysis aws-ec2 certbot-ssl ensemble-machine-learning nginx server
Language:Jupyter Notebook 9
deveshsangwan / Skin-lesions-classification
This repo includes classifier trained to distinct 7 type of skin lesions
convolutional-neural-networks deep-learning ensemble-learning ensemble-machine-learning ensemble-model ham10000 harvard-dataverse inception inception-v3 machine-learning resnet resnet-152 skin-cancer skin-lesion-classification skin-lesions vgg vgg19 xception xception-model
Language:Jupyter Notebook 9
raghavagps / toxinpred3
An improved method for predicting toxicity of the peptides and designing of non-toxic peptides
bioinformatics ensemble-machine-learning machine-learning-algorithms motif-prediction peptide-therapeutics toxicity-prediction
Language:Python 9
abhidtu2014 / Image-splicing-detection-python
Splicing detection | ML
image-processing image-segmentation splicing-detection sift-algorithm zernike cross-validation ensemble-machine-learning machine-learning image-classification binary-classification image-splicing-detection pca-analysis kpca-analysis haralick-features
Language:Python 8
CodeByHarri / Stacking-Ensemble-Machine-Learning
Stacking Machine Learning Models. Tunning; feature engineering, scaling, models combinations and parameters.
machine-learning stacked-generalization ensemble-machine-learning regression-models classification-model
Language:Jupyter Notebook 8
davidmasse / US-supreme-court-prediction
Predicting the ideological direction of Supreme Court decisions: ensemble vs. unified case-based model
categorical-features classification-model curse-of-dimensionality-solution data-leakage ensemble-machine-learning feature-importance pipeline-framework
Language:Jupyter Notebook 8
IvanVigor / Local-Fusion-Dynamic-Weighted-Ensemble
This repository contains an implementation for the Dynamic Weighted Ensemble (DWE) - Local Fusion method. Local Fusion is an ensemble techinque that could be used to improve predictions by weighing appropriately the single models contribution.
anomaly-detection ensemble-machine-learning nuclear python regression-algorithms time-series wind
Language:Python 8
kafisatz / DecisionTrees.jl
Julia Decision Tree Algorithms for Regression
actuarial boosting-algorithms decision-trees decisiontree decisiontrees ensemble-machine-learning julia julialang regression
Language:Julia 8
omarmhaimdat / xgboost_student_performance
Introduction to XGBoost with an Implementation in an iOS Application
coremltools decision-tree-regression ensemble-machine-learning ios-app ios-swift machine-learning python swift xgboost xgboost-algorithm xgboost-python
Language:Swift 8
HarryMills / GASEN
Genetic Algorithm based Selective Neural Network Ensemble
machine-learning genetic-optimization-algorithm nerual-network genetic-algorithm python ensemble-machine-learning
Language:Python 7
wahyudesu / Marketing-Spend-Optimization-using-Machine-Learning
ensemble ensemble-machine-learning marketing optimization python
Language:HTML 5

ensemble-machine-learning

h1st-ai / h1st

sharmapratik88 / AIML-Projects

nikitaprasad21 / ML-Cheat-Codes

ZhiningLiu1998 / mesa

FilippoMB / Ensemble-Conformalized-Quantile-Regression

desh2608 / dover-lap

gkunapuli / ensemble-methods-notebooks

dkanungo / Probabilistic-ML-for-finance-and-investing

louisowen6 / SENN

FernandoLpz / Stacking-Blending-Voting-Ensembles

alicex2020 / Deep-Learning-Lie-Detection

Dan-Boat / PyESD

jon-chun / sentimentarcs_notebooks

AaronWard / PU-learning-example

ashishpatel26 / Most-used-ML-Packages

tonyleidong / OptimalFlow

PradeepThapa / nsl_kdd_classification

action-ai-institute / MABEL-dataset

Haoning724 / obbstacking

Anello92 / Machine_Learning_Python

yashksaini-coder / Mohs-hardness-ensemble-prediction

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

fischlerben / Machine-Learning-Credit-Risk

pm390 / recsys2022

IPVS-AS / pusion

aayush1036 / housing-rent-prediction

deveshsangwan / Skin-lesions-classification

raghavagps / toxinpred3

abhidtu2014 / Image-splicing-detection-python

CodeByHarri / Stacking-Ensemble-Machine-Learning

davidmasse / US-supreme-court-prediction

IvanVigor / Local-Fusion-Dynamic-Weighted-Ensemble

kafisatz / DecisionTrees.jl

omarmhaimdat / xgboost_student_performance

HarryMills / GASEN

wahyudesu / Marketing-Spend-Optimization-using-Machine-Learning