navies-bayes-classifer

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

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…

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.

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

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.

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.

I built a Smart Expense Categorizer using Streamlit and Machine Learning. It uses TF-IDF for text vectorization and Naive Bayes for classification to automatically categorize bank transactions based on given description and spending amount details . after processing the data it predicts the expense categories and downloadable categorized report

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

The objective is to analyze voter behavior based on demographic and opinion-based variables and build a classification model that can predict which party a voter will vote for. This model is used to simulate an exit poll.

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.

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!

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

🐙 Lung cancer prediction with logistic regression using clinical features and feature selection, with robust evaluation metrics. Code and results live in the analysis notebook.

Application of machine learning model, on datasets, to predict desired target variables.

Multi-class classification of news articles using NLP techniques, TF-IDF, and Naive Bayes

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

Python-based personal budget tracker for managing income, expenses, spending categories, and financial goals.

The university assignment that implements models to predict weather Pokémon is legendary or not.