Search Results for "spreadsheet machine learning" - Page 79
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Showing 2009 open source projects for "spreadsheet machine learning"
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A program which retrieves TV program data and asks user which TV programs he / she'll watch that day. Using that data program learns the user preferences using machine learning algorithms (such as support vector machines).
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Zabal6 is a machine learning student tool based on decision tree learning, focused in the area of knowledge discovery (data mining), and inspired on See5. Zabl6 is a C++ program for Linux and windows O.S, with a intuitive graphical interface.
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The Decision Tree Learning algorithm ID3 extended with pre-pruning for WEKA, the free open-source Java API for Machine Learning. It achieves better accuracy than WEKA's ID3, which lacks pre-pruning.Info: http://bruno-wp.blogspot.com/search/label/Softwar
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A discretization algorithm based on the Minimum Description Length. Implemented as a filter according to the standards and interfaces of WEKA, the Java API for Machine Learning. More Info: http://bruno-wp.blogspot.com/search/label/Software
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info thy + machine learning for organization, inference, and analysis of networks. contributed by the wiggins lab, currently @ columbia university, NYC. material supported by NSF #0332479. Any opinions, findings, and conclusions or recommendations expres
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Machine learning toolkit for unsupervised and semi-supervised clustering that demonstrates excellent results on real-world data (see Bekkerman et al. ICML-2005 and ECML-2006).
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The aim of the BioWeka project is to add bioinformatics functionalities such as e.g. alignments to the popular machine learning framework Weka.
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Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.
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A tool for segmenting objects of interest in images, namely creating masks, and storing them for a set of images. It may provide some automatic/interactive segmentation for certain classes of objects. For computer vision / machine learning applications.
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KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
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PCP (Pattern Classification Program) is an open-source machine learning program for supervised classification of patterns. PCP is a binary executable running on Linux and Windows (under Cygwin environment).
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MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning. The code is well documented and easy to extend, especially for adding new weak learners.
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JFex is a feature extraction application for Natural Language Processing systems based on machine learning techniques.
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The Pattern Analysis Library (PALib) is a C++ class library for pattern classification/recognition. PALib consists of a wide range of machine learning routines such as Bayesian decision theory, artificial neural networks, and fuzzy inference systems.
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CompLearn is a general-purpose compression-based machine learning system that uses data compression to learn or data mine patterns in arbitrary data.
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Java library devoted to handle Genetic Algorithms and Classifier Systems. It has been engineered to be used into agent based simulation models and to search bounded optimal solutions in wide solution spaces. It runs on distributed clusters.
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A collection of open source software and documents on machine perception and machine learning. Includes a state of the art face detector (MPISearch), video labeling tools (Score), and tutorials (Kolmogorov Tutorials).
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MLP is a library containing a framework for the development of Machine Learning algorithms as well as a set of standard ML algorithms ready to be used. It is similar in the spirit to the weka project, but it is written in C++.
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FLPD is an automatic learning system based on fuzzy prototypes, composed of a C++ library for machine learning and fuzzy logic and an experimentation framework.
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QuDA, a Data Miners discovery environment. The objective of this project is to support scientific and teaching activities in the field of Machine Learning and Data Mining.
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The TreeQ package is a set of C-language applications that implement a automatic machine learning algorithm based on a tree-structured classifier. This approach is particularly effective for high-dimensional continuous data such as audio and video.
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JUDGE (Java Utility for Document Genre Eduction) features automatic classification and clustering of documents, optionally as a webservice. The program is written entirely in Java and makes use of the Weka machine learning toolkit.
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After the presentation on CeBIT 2004 fair finally available: SpamStop works as a Proxy between your Pop3-Client and the -Provider, it uses a Support Vector Machine to classfy incoming mails and automatically learns classifiers from samples of your mails.
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VFML -- Very Fast Machine Learning toolkit. A collection of tools, learners, and APIs for working with high-speed data streams and very large data sets.
