Search Results for "data analysis and visualizing" - Page 2

...This extracts a relevant structure for both documents (and thus avoids the over-training) which are then compared using the Vector-Space analysis to give a range of belonging of one document to another (and thus avoids the shortage of information). This method can be used to create the user-defined classes by merging texts of certain categories and then to calculate the relevant distances between the documents, but this is not necessary.

LExAu: Learning Expectations Autonomously. Library for on-line data driven statistical machine learning.

This is a GUI for learning non disjoint groups of documents based on Weka machine learning framework. It offers the possibility to make non disjoint clustering of documents using both vectorial and sequential representation (word sequence approach based on WSK kernel). All data format supported by WEKA could be used in DocCO. Data could be loaded from files, from databases or from specified URL. All the preprocessing techniques implemented in WEKA could be used before performing the learning.

feed4weka is an open library that enriches weka (http://www.cs.waikato.ac.nz/ml/weka/), an open source project for data analysis. It integrates new classification and clustering algorithms, and adds the coclustering and outlier detection frameworks

JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.

The FAKE GAME tool uses natural evolution to evolve Data Mining models. It incorporates several preprocessing, optimization and visualization methods aimed to streamline the Knowledge Discovery process. Knowledge Extraction from data is being automated!

The AdPreqFr4SL learning framework for Bayesian Network Classifiers is designed to handle the cost / performance trade-off and cope with concept drift. Our strategy for incorporating new data is based on bias management and gradual adaptation. Starting with the simple Naive Bayes, we scale up the complexity by gradually updating attributes and structure. Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we...

Darwin 2: Java Framework for Evolutionary Computation (genetic algorithm, GA). A true framework with out-of-the-box functionality and extensibility of all classes. Interface-based pattern with dependency-injection to configure components.

Conversion between different grammar frameworks is of great importance to comparative performance analysis of the parsers developed on them. This tool can convert CCG derivations to PTB trees by using Max Entropy models as well as visualizing the tree graphs. The main technical innovation presented here is the effective conversion method which achieves a F score over 95%.

The project includes a software, which uses an AI for autonomous sailing of a small sailing boat, equipped with various sensors and GPS. There are various methods for evaluation and improvement of sensor data, route planning, collision avoidance.

Cougar Squared is a new Java library for machine learning and data mining research, supporting research needs of the community. It is written by researchers for researchers. It extends the WEKA and YALE machine learning frameworks.

A Machine Learning and Data Retrieval Framework

Siafu simulates individual agents and their context, from home to city-wide scenarios. As a developer, you use the API to write your simulation for the purposes of data-set generation, test or visualization, optionally hooking it to your own application.

Tool for visualizing artificial neural networks in Matlab using the Matlab Neural Network Toolbox (see wiki for details).

A java library for the processing and analysis of natural language texts and other sequential data. The focus is on unsupervised modeling with simple, statistical methods as well as implementations of more complex algorithms.

Contextor is a light-weight simple-to-use Java based library to help developers and researchers working with the general concept of a resource; as examples, resources can be text resources, web resources, images and videos.

Open data mining platform. Provides common architecture for algorithms of various types. Efficient processing of arbitrarily large volumes of data thanks to data streaming. Weka and Rseslib partially integrated. (www.debellor.org)

A GUI-based text annotation tool for creating and visualizing annotations. It uses a flexible stand-off XML data format, and has advanced and customizable methods for information and relation visualization.

Photios attempts to aggregate, normalize, analyze, and present system log data in an accessible, searchable, and sortable fashion.

Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.

JUNG provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. New version now available on GitHub: https://github.com/jrtom/jung/releases/tag/jung-2.1

JAVA based tool for easy and realtime monitoring (RTM) of data streams or groups of data streams. This tool makes it easy to monitor inherent distributed or multi-threaded applications like e.g. agent systems, financial data, logistics, RFID Systems

Projeny (Probablistic Networks Generator in Java) is a graphical (Java SWT) front-end to BNT (Bayes Net Toolbox for Matlab). Projeny requires BNT, JMatLink and a Matlab back-end. There is no installable release package, but source code is available on SVN - please check out from SVN to use Projeny. Projeny was started with BNJ as the base.

Blunder is an automated tool for analyzing chained exceptions in Java. It's usefull for classify, generate a customized error message and a list for possible solutions.

Facilitates data mining/natural language processing experiments to be executed on weblogs, such as classification, clustering and rating. As part of these experiments, it is possible to apply Latent Semantic Analysis.