157 Open source projects that are alternatives of or similar to Naive Bayes Classifier

Deep universal probabilistic programming with Python and PyTorch

Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive Language", ICWSM 2017

A PureScript, browser-based implementation of LDA topic modeling.

Seminars DeepBayes Summer School 2018

GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to adress parameter and model uncertainties.

GPstuff - Gaussian process models for Bayesian analysis

Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC

Hierarchical Bayesian modeling of RLDM tasks, using R & Python

Python package for Bayesian Machine Learning with scikit-learn API

Projection predictive variable selection

This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

📜 🎉 Automated reporting of objects in R

The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch

C++ template library for probabilistic programming

📊 Naive Bayes classifier for JavaScript

A high-level Bayesian analysis API written in Python

Machine learning to classify Malicious (Spam)/Benign URL's

Bayesian Data Analysis demos for Python

A collection of research papers on decision, classification and regression trees with implementations.

A collection of Bayesian data analysis recipes using PyMC3

simple rules engine

custom human activity recognition modules by pose estimation and cascaded inference using sklearn API

Bayesian multi-object tracking

A Naive Bayes machine learning implementation in Elixir.

PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty

Matlab interface to Stan, a package for Bayesian inference

👻 Utilities for analyzing Bayesian models and posterior distributions

An R package for experimental psychologists

A Python interface for Facebook fastText

"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).

Machine learning based text classification in JavaScript using n-grams and cosine similarity

A sophisticated smart symptom search engine

Machine learning for Project Cognoma

Scene text detection and recognition based on Extremal Region(ER)

A curated list of data mining papers about fraud detection.

⛔️ ARCHIVED ⛔️ 🐒 R package for text analysis with Monkeylearn 🐒

Gauss Naive Bayes in Python From Scratch.

A Machine Learning classifier for recognizing the digits for humans.

Bayesian Changepoint Detection

licensechecker (lc) a command line application which scans directories and identifies what software license things are under producing reports as either SPDX, CSV, JSON, XLSX or CLI Tabular output. Dual-licensed under MIT or the UNLICENSE.

A curated list of gradient boosting research papers with implementations.

Machine Learning inference engine for Microcontrollers and Embedded devices

How to do Bayesian statistical modelling using numpy and PyMC3

Building classifiers using cancer transcriptomes across 33 different cancer-types

An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more

An interactive online reading of McElreath's Statistical Rethinking

Bayesian Data Analysis demos for R

A repository for recording the machine learning code

Natural language detection library for Rust. Try demo online: https://www.greyblake.com/whatlang/

Tutorial on model assessment, model selection and inference after model selection

A python library for Bayesian time series modeling

The posterior R package

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

Object classification with CIFAR-10 using transfer learning

A simple web app that shows how Watson's Natural Language Classifier (NLC) can classify ICD-10 code. The app is written in Python using the Flask framework and leverages the Watson Developer Cloud Python SDK

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. Now almost entirely superseded by the models-by-example repo.

The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox.

A general-purpose probabilistic programming system with programmable inference

Udacity Self-Driving Car Engineer Nanodegree. Project: Vehicle Detection and Tracking