Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm.

Last update: Jun 27, 2022

Related tags

Overview

Naive-Bayes Spam Classificator

Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm. Main goal is to code a spam filter from scratch that classifies messages with an accuracy greater than 90%.

Main files

This project contains 2 modules:

bayesian_classifier.py -- BayesianClassifier class which is used to classify whether the message is spam or ham. It also calculates model score for accuracy.
main.py -- main file for running the programm.

How does it work?

After running a program, Spam Classificator provides the user with 2 options:

to test a model on data base and get model score;
to test a model on statement the user inputs;

If there are many words in the statement that are not present in the database, then the program will most likely output ‘needs human classification, probably spam’.

Owner

Viktoria Maksymiuk

GitHub Repository

Regularization and Feature Selection in Least Squares Temporal Difference Learning

Regularization and Feature Selection in Least Squares Temporal Difference Learning Description This is Python implementations of Least Angle Regressio

0 Jan 18, 2022

Test symmetries with sklearn decision tree models

Test symmetries with sklearn decision tree models Setup Begin from an environment with a recent version of python 3. source setup.sh Leave the enviro

2 Jul 19, 2022

Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class

482 Nov 19, 2022

My capstone project for Udacity's Machine Learning Nanodegree

MLND-Capstone My capstone project for Udacity's Machine Learning Nanodegree Lane Detection with Deep Learning In this project, I use a deep learning-b

407 Dec 12, 2022

A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!

Stox A Module to predict the "close price" for the next day and give "technical analysis". It uses a Neural Network and the LSTM algorithm to predict

31 Dec 16, 2022

PROTEIN EXPRESSION ANALYSIS FOR DOWN SYNDROME

PROTEIN-EXPRESSION-ANALYSIS-FOR-DOWN-SYNDROME Down syndrome (DS) is a chromosomal disorder where organisms have an extra chromosome 21, sometimes know

1 Jan 20, 2022

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

1.3k Dec 22, 2022

Distributed deep learning on Hadoop and Spark clusters.

Note: we're lovingly marking this project as Archived since we're no longer supporting it. You are welcome to read the code and fork your own version

1.3k Dec 28, 2022

Empyrial is a Python-based open-source quantitative investment library dedicated to financial institutions and retail investors

By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated

640 Dec 31, 2022

Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

10 May 15, 2022

Module is created to build a spam filter using Python and the multinomial Naive Bayes algorithm.

Related tags

Overview

Naive-Bayes Spam Classificator

Main files

How does it work?

Owner

Viktoria Maksymiuk

Regularization and Feature Selection in Least Squares Temporal Difference Learning

Test symmetries with sklearn decision tree models

Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

My capstone project for Udacity's Machine Learning Nanodegree

A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!

PROTEIN EXPRESSION ANALYSIS FOR DOWN SYNDROME

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

Distributed deep learning on Hadoop and Spark clusters.

Empyrial is a Python-based open-source quantitative investment library dedicated to financial institutions and retail investors

Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python

jaxfg - Factor graph-based nonlinear optimization library for JAX.

A basic Ray Tracer that exploits numpy arrays and functions to work fast.

Machine-learning-dell - Repositório com as atividades desenvolvidas no curso de Machine Learning

Python-based implementations of algorithms for learning on imbalanced data.

Confidence intervals for scikit-learn forest algorithms

Practical Time-Series Analysis, published by Packt

2021 Machine Learning Security Evasion Competition

Book Item Based Collaborative Filtering