GitHub topics: bagging-classifier
Param-Sahu/Exit_Poll_and_Vote_Prediction_Model
The objective is to analyze voter behavior based on demographic and opinion-based variables and build a classification model that can predict which party a voter will vote for. This model is used to simulate an exit poll.
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Szymon-Czuszek/Machine-Learning-Algorithms
In this repository, I will share the materials related to machine learning algorithms, as I enrich my knowledge in this field.
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CamilaJaviera91/bagging-with-kaggle
Code in which an initial approach to decision trees and bagging will be made, and an attempt will be made to ensure that the model can be trained with any dataset coming from Kaggle (for this, we will again use the 'connect with Kaggle' project).
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Relostar-Devil/Bio-Signal-Analysis-for-Smoking
Unlocking Insights into Smoking with Bio-Signals: Journey through health data to predict smoking habits. Employing machine learning and feature selection to identify smokers.
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ozturkfemre/classification
R | Classification Project
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sarahloree/Project-3--Credit-Card-User-Churn-Prediction
This is the third project I completed as part of the Advanced Machine Learning module from my post-graduate certification in AI/ Machine Learning from University of Texas' McCombs School of Business.
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rjlovespy/Astro-Entity-Classifier
A Tkinter based ML tool that classifies astronomical entities as Galaxy, Star, and Quasar
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djdhairya/Crop-Recommendation
Crop Recommendation System is a powerful tool for enhancing agricultural decision-making. By leveraging data-driven insights, it empowers farmers to maximize yield and ensure sustainable practices.
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vignesh4005/Crowdfunding_Campaign_Success_Prediction
This project aims to predict the success of crowdfunding campaigns using machine learning models: Ensemble Learning, Naive Bayes, and Support Vector Machine (SVM).
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spamfromaditya/Drugs-Consumption-Prediction-Model-EDA-Bagging-Classifier
Drug consumption prediction models are like crystal balls for public health. By analyzing vast amounts of data, these models can identify individuals or communities at higher risk of drug use. They consider factors like demographics, social media activity, prescription history, and even economic indicators.
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AmbreenMahhoor/Bagging-Ensemble
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prajwalp3/Cardiovascular-Disease-prediction-using-Machine-learning-models
Our project utilizes machine learning models to predict cardiovascular diseases (CVDs) by analyzing diverse datasets and exploring 14 different algorithms. The aim is to enable early detection, personalized interventions, and improved healthcare outcomes.
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Keerthiga-Sekar/-Predicting-Employees-Preferred-Mode-of-Transport-
Analyze the data of ABC consulting company, build a predictive model based on the parameters like age, salary, work experience and predict the preferred mode of transport.
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hugohiraoka/Travel_Package_Purchase_Prediction
Model to Predict if a customer will purchase a Travel Package
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SophiaRazzaq/Landslide-Insights-and-Prediction
Machine Learning
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ArchismwanChatterjee/Parkinson_Detection
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rociobenitez/BiomechanicalRiskPrediction
Predictive Analysis for Musculoskeletal Injury Risk using Machine Learning and Flask
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meAnubhav/Heart_Disease_Prediction_by_Machine_Learning
A machine learning application, deployed using Flask, is designed to identify the presence of heart disease in patients by analyzing various medical features.
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ShababAhmedd/CSE437_DataScience
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vicaaa12/advanced-machine-learning
Advanced Machine Learning
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Ashwin0229/Tree-Classifiers
Comparative Analysis of Decision Tree Algorithms in Number Classification: Bagging vs. Random Forest vs. Gradient Boosting Decision Tree Classifiers
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Sarthak-10/Bagging-Classifier-from-scratch
The project contains an implementation of Bagging Classifier from scratch without the use of any inbuilt libraries.
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niveditha093/VisaApproval
Visa approval process by leveraging machine learning on OFLC's extensive dataset, aiming to recommend suitable candidate profiles for certification or denial based on crucial drivers.
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Yalda-amadeh/Shatel-dataset
Some process on Shatel dataset.
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Atif255/Titanic-Survival-Prediction
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nielsxklesper/Machine_Learning_Challenge
Our group project aimed to evaluate three predictive machine learning classification models to anticipate whether website visitors engage in transactions. This is done by analysing different attributes of website visitors including duration spent on different web pages, click rates, and bounce rates.
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GyanPrakashkushwaha/Customer-Churn-Prediction
Customer Churn Prediction using Machine Learning and Deep learning. With Integration of MLFlow
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vasatodorovic/ToxicityOfMolecules
Project on course "Data Mining 2"
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vasupatelll/Email_Spam_Classifier
A Machine Learning Processing with SMS Data to predict whether the SMS is Spam/Ham with various ML Algorithms like MultinomialNB, LogisticRegression, SVC, DecisionTreeClassifier, RandomForestClassifier, KNeighborsClassifier, AdaBoostClassifier, BaggingClassifier, ExtraTreesClassifier, GradientBoostingClassifier, XGBClassifier to compare accuracy an
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lucoliv23/KC-Roasters-Classification-
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RawatMeghna/Flight-Booking-Price-Prediction
The project is to analyze the flight booking dataset obtained from a platform which is used to book flight tickets.
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amondalgit/DMML23-assignments
Data Mining Machine Learning | Assignments | JAN-APR 2023 | CMI
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DWalicki95/Titanic_case_study-alghoritms-comparison-
Titanic survivors binary classification
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ZeeshanKhalid2k01/Bagging
Bagging is the term from "Bootstrap Aggregation Algorithm", That is for Low Bias & Low Variance
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LALA09-erha/Streamlit---WebPrediksiKNN
Website Prediksi Penyakit jantung dengan 5 fitur menggunakan metode KNN,bagging classifier,random forest
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anandanraju/Eligibility_Validation_Report_Model_for_Borrowing_Money_From_Bank
In simple, a Loan (borrowing money from a bank) is the sum of money that you borrow from the bank or lending financial institution in order to meet needs. These needs could result from planned or unplanned events, and by borrowing, you incur a debt that you have to pay within the agreed duration on your contract.
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anandanraju/Titanic_Survival_Prediction_Model
The sinking of the RMS Titanic is one of the most infamous shipwrecks in world history. In this model, need to analyse what sorts of people were likely to survive. We also need to apply the tools of machine learning to predict which passengers survived in this tragedy.
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sean-atkinson/supervised_learning_models
Playing around with a variety of classification and regression models.
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