A research project of anomaly detection on dataset IoT-23

Heart disease prediction and Kidney disease prediction. The whole code is built on different Machine learning techniques and built on website using Django

We took an iris dataset and trained with different classifiers to find out their accuracy and some parameters.

This repo is the Machine Learning practice on NHANES dataset of Heart Disease prediction. The ML algorithms like LR, DT, RF, SVM, KNN, NB, MLP, AdaBoost, XGBoost, CatBoost, LightGBM, ExtraTree, etc. The results are good. I also explore the class-balancing (SMOTE) because the original dataset contains only 5% of patient and 95% of healthy record.

The cancer like lung, prostrate, and colorectal cancers contribute up to 45% of cancer deaths. So it is very important to detect or predict before it reaches to serious stages. If cancer predicted in its early stages, then it helps to save the lives. Statistical methods are generally used for classification of risks of cancer i.e. high risk or l…

A Flask based production level web app which uses Naive Bayes classifier to predict given SMS is spam or ham. Also contains jupyter notebook with basic data exploration and ml modelling.

Welcome to the "SMS Spam Detector" project! This machine learning model identifies whether a given SMS is spam or not, providing a valuable tool for spam detection and filtering.

Sklearn, logistic regression, Naive Bayes classifier, K-Nearest Neighbors, decision trees

A Model Built Using Kaggle Dataset & Machine Learning Classification Algorithms such as Logistics Regression,K-NN, Naive Bayes, SVM, Decision Tree & Random forest which Predicts chances of heart disease in a person.

Movie genre classification in NLP using multinomial navie bayes classification and linear support vector classification.

Indian English News (2023) Analysis and Classification: Categorize news articles with class labels like entertainment, social, sports, national, etc. Achieved 83% accuracy. Interactively predict categories from headlines. Contributions welcome!

This repository contains a machine learning model developed using the Pima Indians Diabetes dataset. The goal of this project is to predict the likelihood of diabetes in patients based on various medical attributes.

This repository consists of various projects based on Machine Learning and NLP.

Spambase dataset analysis comparing Naïve Bayes classifiers. Evaluated accuracy, confusion matrices on different splits. Explored alternatives for improved performance in ML course, uOttawa 2023.

spam/ham classifier

Link Analysis, Naive Bayes Text Classifier, Marathi Stemmer

Labs for ECS763 Natural Language Processing

Detect email phising use Navie Bayes, RF, SVM, ANN and Decicion Tree. Dataset use Enron email.

The project focuses on sentiment analysis of Coronavirus tweets NLP - Text Classification kaggle dataset