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).

A machine learning project that predicts results of a football match

AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset

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

This is a Malware Detection ML model made using Random Forest Algorithm

A random forest classifier to identify contigs of plasmid origin in contig and scaffold genomes

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.

Implementation of various machine learning algorithms to predict the disease from symptoms.

Technic analyzer with ML (RTF) and signal sender bot using telegram

Similarity based email sorting for Google Mail using RandomForest classifiers

Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties

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…

Machine learning library for classification tasks

A web app for Flight Delay Prediction using Random Forest Classifier

Various Classification models used are Logistic regression, K-NN, Support Vector Machine, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification using Python

Website Prediksi Penyakit jantung dengan 5 fitur menggunakan metode KNN,bagging classifier,random forest

In this project, the success results obtained from SVM, KNN and Decision Tree Classifier algorithms using the data we have created and the results obtained from the ensemble learning methods Random Forest Classifier, AdaBoost and Voting were compared.