There are 0 repository under stacking-classifier topic.
This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regression) and Machinery Fault Dataset dataset available on kaggle.
Advancing Cybersecurity with AI: This project fortifies phishing defense using cutting-edge models, trained on a diverse dataset of 737,000 URLs. It was the final project for the AI for Cybersecurity course in my Master's at uOttawa in 2023.
A web application to predicted whether a URL/Website is phishing or not by extracting its lexical features.
使用比赛方提供的脱敏数据,进行客户信贷流失预测。
AS-DMF framework guide
This repository provides a complete pipeline for non-invasive blood glucose estimation using Photoplethysmography (PPG) signals. It includes data preprocessing, feature extraction, machine learning model training, and result visualization to support research and development in biomedical signal analysis and diabetes screening.
Classification Modeling: Probability of Default
This project is dedicated to accurately classify Alzheimer's disease into Demented, Non-demented and Converted Category.
This project focuses on predicting the likelihood of diabetes in individuals using ensemble machine learning models. It combines various ensemble techniques, including Random Forest, AdaBoost, Gradient Boosting, Bagging, Extra Trees, XGBoost, Voting Classifier and some others to get predictions.
Final Project Of Computational Intelligence - Fall 2021 - LightGBM, RandomForest and StackingClassifier
Android malware detection using machine learning.
Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.
This project aims to predict the selling prices of used cars based on various features such as brand, model year, mileage, and engine specifications.using-Stacking-ensemble-modeling-technique
This repository contain my final projekt on the Data science Skillbox school on the topic: "Development of a machine learning algorithm to predict the behavior of customers of the "SberAvtopodpiska"
This is just a theoretical Machine Learning Model that will analyze the data and determine where the stroke can occur.
This project presents a ML based solution using Ensemble methods to predict which visa applications will be approved and thus recommend a suitable profile for applicants whose visa have a high chance of approval
Prediction-of-House-Grade-Classification using python ( Jupyter Notebook)
A ML/DL project that predicts Poker Hand rankings based on given card combinations.
Analyzed time-series data (Depressjon) to detect depression from patient activity recorded via clinical actigraphy watches. Utilized features such as time domain, statistical metrics, and LSTM-extracted attributes.
I present a statistical analysis and machine learning prediction for a diabetes dataset from Kaggle.
This project focuses on detecting and classifying brain tumors (NonDemented, Very Mild Demented, Mild Demented, Moderate Demented)
Using classical machine learning techniques for classifying the data into 9 classes which can be further used for cancer detection.
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.
My AIML Journey
A Machine Learning project for Cardiovascular disease prediction
Detecting and Identifying Fraudulent credit card transactions from normal transactions.
Evaluating Traditional and Ensemble Learning Techniques for Churn Prediction
This repository includes the implementation of stacking individual ML models Random forests as an ensemble techniques.
The Office of Foreign Labor Certification is facing a dramatic increase in work visa applications, but is hampered by a sluggish review system. It needs to improve the process by developing a way to quickly, accurately identify applications likely to be accepted or rejected so their processing may be prioritized.
Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.
Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.
Plastic-covered cropland detection using satellite imagery and stacking classifiers – FAO GeoAI 2024 Challenge.
Code of model stacking for Kaggle Competition
Ensemble Techniques: Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.