Search Results for "artificial intelligence algorithm" - Page 2
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Showing 141 open source projects for "artificial intelligence algorithm"
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JinnIde is a plugin that allows using Jinni Prolog, now also hosted here on this site (with open source license!), within the confines of an IDE integrated in JEdit.
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HAWK - PDF Text Search Java Project
No more support for this project - TAKE A LOOK AT FALCONSEARCH
No more support for this project - TAKE A LOOK AT FALCONSEARCH "https://sourceforge.net/projects/falcontextsearch/" -
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Weka4OC GUI for Overlapping clustering
Weka4OC: Weka for Overlapping Clustering is a GUI extending WEKA
This is a GUI application for learning non disjoint groups based on Weka machine learning framework. It offers a variety of learning methods, based on k-means, able to produce overlapping clusters. The application also contains an evaluation framework that calculates several external validation measures. The application offers a visualization tool to discover overlapping groups. -
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ktree
clustering, machine learning, algorithms
This project has moved to github at http://lmwtree.devries.ninja. -
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Unsupervised TXT classifier
Classify any two TXT documents, no training required - JAVA
This program is made to address two most common issues with the known classifying algorithms. First, over-training and second, shortage of data for a training of categories. Instead, each TXT file is a category on its own, rather than an assigned category. In a way, this is similar to clustering but not really a clustering algorithm since there is some training involved. The summarizer from Classifier4J has been adjusted to accept two inputs (lets call them A and B). Then, the summarizer... -
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LExAu: Learning Expectations Autonomously. Library for on-line data driven statistical machine learning.
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DocCO
Non-disjoint groupping of Documents based on word sequence approach
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. -
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This is a GUI, Java implementation of the Ant Colony Optimisation/Particle Swarm Optimisation (PSO/ACO2) rule induction algorithm. This project was inspired by Ant-Miner, but handles continuous attributes using PSO or now Differential Evolution.
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ABC-DynF
Adaptive Bayesian Classifier with Dynamic Features
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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!
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AdPreqFr4SL
Adaptive Prequential Learning Framework
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... -
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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.
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JBoost is a simple, robust system for classification. JBoost contains implementations of several boosting algorithms in an alternating decision tree framework. In addition, JBoost provides extensible software for adding more learning algorithms.
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ssSVMToolbox is a Java application capable of performing supervised and semi-supervised learning tasks with Support Vector Machines. It is based on Spring (http://springframework.org/), RapidMiner (http://www.rapidminer.com) and Eclipse RCP (http://eclip
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The Wikipedia Miner toolkit provides simplified access to Wikipedia. This open encyclopedia represents a vast, constantly evolving multilingual database of concepts and semantic relations; a promising resource for nlp and related research.
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SIM-DL: Semantic Similarity Measurement Server for concepts (and individuals) represented using (expressive) Description Logics (DL).
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SEMANTIXS is a semantic information extraction system that can extract, represent and visualize domain-specific information from free-text in the form of complex (and simple) relationships. Refer - http://www.cs.iastate.edu/~semantix/ for more info.
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TextMarker is now developed and hosted at Apache UIMA (http://uima.apache.org/textmarker.html). TextMarker is a UIMA-based tool for information extraction and more. The full featured editor of the rule language and the build process of UIMA descriptors are complemented with components for visualization, explanation, testing and rule learning.
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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.
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Feating constructs a classification ensemble comprising a set of local models. It is effective at reducing the error of both stable and unstable learners, including SVM. For details see the paper at http://dx.doi.org/10.1007/s10994-010-5224-5.
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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.
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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.
