UploadLanguage (EN)Support

Change Language

Language

Machine Learning Insights | Random Forest

The collection explores diverse applications of machine learning algorithms, particularly focusing on the random forest technique across various domains such as healthcare, agriculture, and cybersecurity. Topics include predictive modeling for heart diseases, fraud detection, crop yield estimation, and early diagnosis of conditions like diabetes and asthma. The emphasis is on enhancing accuracy through novel methodologies, addressing challenges such as data balance and feature selection, and showcasing the potential of these algorithms in practical decision-making and analysis.

Increased Prediction Accuracy in the Game of Cricket Using Machine Learning
byIJDKP
 
Optimization and Validation of Two Machine Learning Algorithms for Accurate Prediction of Irrigated Wheat (Triticum aestivum L.) Yield and Identification of its Influential Factors in Khorasan Razavi Province
byIran. J. Field Crops Research
 
AI-POWERED MODELS FOR EARLY DETECTION OF CAD
byijsc
 
Diabetes_Project_Presentation dataset fr
bykaurmultani222
 
A Comparative Study of Random Forest and XGBoost for Detecting Credit Card Fraud Transactions using Big Data | Mohamed Riham - CRP Final Presentation.pptx
byMohamed Riham
 
Predictive model for converting leads into repeat order customer using machine learning
byIJICTJOURNAL
 
Ensemble stacking classifier model for prediction of diabetes
byIJICTJOURNAL
 
Fault detection in single-hop and multi-hop wireless sensor networks using a deep learning algorithm
byIJICTJOURNAL
 
Prediction of land suitability for food crop types using classification algorithms
byTELKOMNIKA JOURNAL
 
Comparative analysis of heart failure prediction using machine learning models
byIJICTJOURNAL
 
Grid search vs Bayesian optimization for intensity scoring classification and channel recommendation prediction
byTELKOMNIKA JOURNAL
 
ML-Lecture 1- Decision Tree and Random Forest.pdf
byZahra Sadeghi
 
Exploring the Random Forest: Ensemble at Its Best
byKumariShivangi5
 
Mastering Random Forest Step by Step
byKumariShivangi5
 
Mastering Decision Trees: From Root to Leaf
byKumariShivangi5
 
Unit 3_Classification - Random Forest_Adaboost.pdf
byKanchanPatil34
 
Optimizing firewall timing for brute force mitigation with random forests
byIAESIJAI
 
Performance analysis and comparison of machine learning algorithms for predicting heart disease
byIAESIJAI
 
Integrating random forest and genetic algorithms for improved kidney disease prediction
byIAESIJAI
 
Shell Battery Peformance using Machine Learning Techniques
bysmtplltd