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GitHub topics: voting-regressor

ArunabhaPani/House_price_prediction_kaggle_learning

started by analysing and determining the aspects required for tuning of the final ml model. Performed Eda and feature engineering inorder to determine the import parameters of the dataset and to derive more useful features, finally creating a ml model by using various different basic and advanced regression techniques.

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Snigdho8869/Regression-Analysis-Projects

Repository showcasing a collection of diverse regression analysis projects including salary prediction and more.

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dileepNaiduOne/BUDGET-app

BUDGET : VotingRegressor(XGBoost+LightGBM) * (5 Fold CV) — This model, built for a Kaggle insurance regression competition, preprocesses data by imputing missing values (KNN), cleaning, and engineering new features. Statistical analysis reduces features before encoding and scaling for machine learning

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sayande01/Ensemble_Learning_ML

This project investigates ensemble learning techniques, combining multiple models to enhance accuracy and robustness. It covers both basic methods (Max Voting, Averaging, Weighted Averaging) and advanced techniques (Stacking, Blending, Bagging, Boosting), aiming to improve predictive performance by addressing model weaknesses.

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samidulloabdullaev/Flights_Arrival_Delay_regression-

This project aims to predict flight arrival delays using various machine learning algorithms. It involves EDA, feature engineering, and model tuning with XGBoost, LightGBM, CatBoost, SVM, Lasso, Ridge, Decision Tree, and Random Forest Regressors. The goal is to identify the best model for accurate predictions.

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LuluW8071/Laptop-Price-Prediction

A collection of machine learning models for predicting laptop prices

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jodiambra/Sweet-Lift-Taxi-Time-Series-Predictions

Time series modeling to predict fares for Sweet Lift Taxi Company. Predictions will be used to allocate drivers for peak hours.

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shreyash2610/-A-Fine-Windy-Day-HackerEarth

Problem Moving from traditional energy plans powered by fossils fuels to unlimited renewable energy subscriptions allows for instant access to clean energy without heavy investment in infrastructure like solar panels, for example. One clean energy source that has been gaining popularity around the world is wind turbines. Turbines are massive structures that are strategically placed in perpetually windy places to generate the most energy. Wind energy is generated when the power of the atmosphere’s airflow is harnessed to create electricity. Wind turbines do this by capturing the kinetic energy of the wind. Factors such as temperature, wind direction, turbine status, weather, blade length, etc. influence the amount of power generated.

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trizkynoviandy/university-admission-prediction

Predict the university admission using machine learning

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anjrew/Bike-Sharing-Demand-Regression

Creates a model used to forecast use of a city bike-share system at any given hour depending on environmental conditions with machine learning 🚴

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kalhorghazal/Artificial-Intelligence-Course-Projects

👩‍💻Artificial Intelligence Course Projects, University of Tehran

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kalhorghazal/House-Price-Prediction

🏡House Price Prediction, Artificial Intelligence course, University of Tehran

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MrRaghav/media-memorability

MediaEval challenge 2019 - to predict the memorability of the Videos

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Pradnya1208/House-prices-prediction

Predict sales prices and practice feature engineering and advanced regression techniques.

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cnrkaya/video-transition-time-estimation

Video transition time estimation with different regression techniques

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Related Keywords
voting-regressor 15 machine-learning 7 linear-regression 6 regression 6 random-forest 5 gradient-boosting-regressor 4 xgboost-regression 4 xgboost 4 machine-learning-algorithms 3 lightgbm 3 regression-models 3 ridge-regression 3 random-forest-regressor 3 python 3 stacking-ensemble 2 catboost 2 scikit-learn 2 streamlit 2 ensemble-learning 2 lasso-regression 2 house-price-prediction 2 knn-regression 2 decision-tree 2 pandas 2 random-forest-regression 2 keras 2 knn 2 fine-windy-day 1 hackerearth 1 numpy 1 data-analysis 1 naive-bayes-classifier 1 data-science 1 a-star-algorithm 1 knn-classification 1 bfs 1 ids-search-algo 1 genetic-algorithm 1 feedforward-neural-network 1 svr 1 extratreesregressor 1 skewness 1 scaling 1 correlation 1 video-memorability 1 tf-idf 1 spearman-rank-correlation 1 neural-networks 1 multimediaeval 1 mediaeval 1 hmp 1 ensemble-models 1 decision-trees 1 count-vectorizer 1 captions 1 c3d 1 kaggle 1 k-nearest-neighbours-regressor 1 decision-tree-regressor 1 voting-classifier 1 tableau 1 optuna 1 ml 1 git 1 tensorflow 1 regression-trees 1 regression-analysis 1 regression-algorithms 1 deeplearning 1 deep-learning-regression 1 deep-learning 1 stackingregressor 1 pipeline 1 gaussian-naive-bayes 1 feature-engineering 1 exploratory-data-analysis 1 ensemble-machine-learning 1 data-visualization 1 boosting-tree 1 beginner 1 time-series 1 seasonality-analysis 1 gradient-boosting 1 adaboost 1 svm-regressor 1 sckiit-learn 1 multiple-linear-regression 1 laptop-price-prediction 1 extra-tree-regressor 1 decision-tree-regression 1 adaboost-regressor 1 lightgbm-regressor 1 catboost-regressor 1