There are 3 repositories under random-forest-classifier topic.
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
Learning to create Machine Learning Algorithms
The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
Machine learning approach to detect whether patien has the diabetes or not. Data cleaning, visualization, modeling and cross validation applied
A machine learning project that predicts results of a football match
Final Year Project on Road Accident Prediction using user's Location,weather conditions by applying machine Learning concepts.
AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset
Some example projects that was made using Tensorflow (mostly). This repository contains the projects that I've experimented-tried when I was new in Deep Learning.
Detect the onset of possible risk of Parkinson's disease with the help of clinical data using Machine Learning Models.
Detect Fraudulent Credit Card transactions using different Machine Learning models and compare performances
A machine learning web application use to predict chances of heart disease, built with FLASK and deployed on Heroku.
An AI-driven platform offering crop recommendations, fertilizer suggestions, and disease detection for optimal farming
#FakersGonnaFake: using simple statistical tools and machine learning to audit instagram accounts for authenticity
URI-URL Classification using Recurrent Neural Network, Support Vector and RandomForest. The Implementation results follows with classification report, confusion matrix and precision_recall_fscore_support for each validation result of a 10-fold crossval
Recognition of Persomnality Types from Facebook status using Machine Learning
Heart disease prediction using normal models and hybrid random forest linear model (HRFLM)
A simple machine learning model for small-molecule target prediction in Python.
This is a Malware Detection ML model made using Random Forest Algorithm
IDS Alert Prioritization INSuRE Research Project
A random forest classifier to identify contigs of plasmid origin in contig and scaffold genomes
In this data set we have perform classification or clustering and predict the intention of the Online Customers Purchasing Intention. The data set was formed so that each session would belong to a different user in a 1-year period to avoid any tendency to a specific campaign, special day, user profile, or period.
Here are the codes for the "Deep Forest classifier for wetland mapping using the combination of Sentinel-1 and Sentinel-2 data" paper.
Implementation of a Random Forest classifier in both Python and Scala
Technic analyzer with ML (RTF) and signal sender bot using telegram
Analysis and classification using machine learning algorithms on the UCI Default of Credit Card Clients Dataset.
Implementation of various machine learning algorithms to predict the disease from symptoms.
Natural Language Processing for Multiclass Classification: A repository containing NLP techniques for multiclass classification of text data.
The purpose of this project is to be able to automatically and efficiently segment and classify high-grade and low-grade gliomas.
Similarity based email sorting for Google Mail using RandomForest classifiers
A machine learning exercise using the Spotify "hit predictor" dataset, with data analysis of past "hits" by decade. Deployment using Flask via Heroku.
I have used Multinomial Naive Bayes, Random Trees Embedding, Random Forest Regressor, Random Forest Classifier, Multinomial Logistic Regression, Linear Support Vector Classifier, Linear Regression, Extra Tree Regressor, Extra Tree Classifier, Decision Tree Classifier, Binary Logistic Regression and calculated accuracy score, confusion matrix and ROC(Receiver Operating Characteristic) and AUC(Area Under Curve) and finally shown how they are classifying the tweet in positive and negative.
Supplementary material for IEEE Services Computing paper 'An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware'
Finding which songs I like or not based on songs statistics
INSAID Assignment to create a ML model to detect fraud transactions for a financial company.
Algerian Forest Fire Prediction
A machine learning model created with random forest classifier to show the probability and predict if an email is spam or non spam