random-forest-classification

Predict your diseases based on the symptoms provided And Image Processing technique is used to predict the skin cancer

A Data Mining Streamlit Application for Astrophysical Prediction using Random Forest Classification in Python

Audio Pattern Recognition project - Music Genres Classification

Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python

Three-dimensional scatter plot visualization of dataset and predict of different machine learning models on diabetes data

AI-NIDS is an advanced student-built cybersecurity project that uses a Random Forest ML model to detect malicious network traffic from the CIC-IDS dataset. It combines real-time attack simulation, visual analytics, and Explainable AI via Groq LLM to deliver SOC-style, human-readable threat explanations—like a virtual security analyst in action.

random forest classification (with hyperparameter tuning) on heart disease dataset.

Machine learning framework for predicting water pipe failure likelihood and prioritizing infrastructure inspection using EPA ECHO-modeled attributes.

Machine learning algorithms implemented in python. Some are implemented in R. Algorithms include XGBoost, Convolutional Neural Network, Recursive Neural Network, Support Vector Machine, K-nearest neighbors, Naive Bayes, Natural Language Processing

A Regression based Machine Learning Algorithm for SPAM and malicious content detection, featuring Logistic Regression & Random Forest Classification training sequences.

Suppose you have are put incharge of a Mars rover Navigation team. And for the navigation model to find the best path you have to classify which paths are safe, where to slow down and where it is dangerous.

Minimal implementation of Random Forest classifier using decision stumps and bootstrap sampling without sklearn.