Search Results for "machine learning predictive" - Page 37

...Play the first song from the Now Playing list, it'll recommend you next songs from the same list. NOTE: MAKE SURE THAT SONG SHUFFLE IS TURNED OFF WHILE USING PRONAC. Based upon K-Nearest Neighbor Machine Learning Algorithm, K-Fold Cross Validation and EchoNest for audio features.

Redundancy due to cut-paste operations in text creates bias in machine learning for NLP. This module takes a directory and produces a subset of the files in that directory (in a list) with an upper bound on similarity between two files.

A vocabulary tree for image classification have been designed to be integrated in mobile robotic applications. It is a learning schema based on decission trees, bags of features and inverted files. The design provides training and optimization parameters that have been characterized using several detectors and descriptors for several input datasets. Evaluation tests performed on public image databases allow to compare obtained results with previously published literature. All the tools...

mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3.

Adobe Malware Classifier is a command-line tool that lets antivirus analysts, IT administrators, and security researchers quickly and easily determine if a binary file contains malware, so they can develop malware detection signatures faster, reducing the time in which users' systems are vulnerable. Malware Classifier uses machine learning algorithms to classify Win32 binaries – EXEs and DLLs – into three classes: 0 for “clean,” 1 for “malicious,” or “UNKNOWN.” The tool was developed using models resultant from running the J48, J48 Graft, PART, and Ridor machine-learning algorithms on a dataset of approximately 100,000 malicious programs and 16,000 clean programs. ...

Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.

This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios. Its intended area of application is in research and education.

SuStorID is an advanced Intrusion Detection System (IDS) for web services, based on machine learning. Its name comes from the term “Su Stori”, which in Sardinian language means “The Falcon”. It’s version is experimental, but demonstrates a number of interesting features, that can be readily exploited to detect and act against web attacks. SuStorID can be coupled with modsecurity, the well known web application firewall, to gather training data and provide for real-time counteractions. ...

The intention of this project is to give all serious users of the SNNS a place where they find a bugfix and patch management and where they get useful information about the SNNS.

PyPR - Python Pattern Recognition. A small collection of useful pattern recognition methods. The code is still in its early stages.

Framework for making Windows applications that are one .exe file in AutoHotKey_L,C++,C#, VB.NET,Java,Groovy,Common Lisp,Nemerle,Ruby,Python,PHP,Lua,Tcl,Perl,Jint,S#,WSH VBScript,HTML/JavaScript/CSS,COM, PowerShell without compiling . For .NET 4.

Simplex method - Linear programming UFU - Learning Machine - Mestrado

An agent-based situated language learning simulation that focuses on lexical learning and grounding, featuring a unigram syntax structure and a CFG-based semantic grammar. Created as a MSc thesis project, using python.

A tool kit to cause problems on a Linux machine for the purpose of gaining professional experience trouble-shooting issues in a controlled manner. This kit is useful in learning how to solve problems before they occur on a production system.

This project consists in a set of challenges to recognize images acquired from 3d Lasers.

The Python Computer Vision Framework is an opened project deisgned for all those interested in computer vision. It aims at making computer vision more easy and structured and matlab-free. It may also be used for other artistic and scientific areas.

Yann is Yet Another Neural Network. Yann is a library to create fast neural networks. It is also a GUI to easily create, edit, train, execute and investigate networks. Multiple topologies, runtime properties and ensemble learning are supported.

Onyx is for rapid prototyping and large-scale experimentation on advanced machine-learning algorithms with an emphasis on algorithms for online or streaming analysis, modeling, and classification.

This program classifies automatically a paper article in one section.

Monte is machine learning in pure Python. Monte's focus is the construction of gradient based learning machines from many small components.

A three-step approach towards experimental brain-computer-interfaces, based on the OCZ nia device for EEG-data acquisition and artificial neural networks for signal-interpretation.

NeuroKiwi is the application of the Associative Model (AM, previously dubbed AMDroid), being a model storing relational change-detections. The application tries to emulate ground-up knowledge accumulation with limited or no prior knowledge of shapes or patterns.

This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.

Spider that recollects data from MySpace Social Network. At now, it is only designed to extract information from native american people because it is used for a social science study in the UNAM (Universidad Nacional Autónoma de México).

A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.