Search Results for "classification"
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Showing 10 open source projects for "classification"
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MOA - Massive Online Analysis
Big Data Stream Analytics Framework.
A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning. -
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Faum
Fast Autonomous Unsupervised Multidimiensional Classification
This is the proof-of-concept implementation of the FAUM Clustering method. This implementation was used to perform the published results and is now released in the hope that it will be useful. -
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SentimentAnalysis-Rick&Morty
Rick & Morty Sentiment Analysis - End-of-Degree Project - UNIR
...Text mining is a fascinating application of data analysis that extracts relevant information from related writings in different linguistic contexts. And therefore, in natural language processing, sentiment analysis and classification stands out as a key application supported by text mining. Through the extraction of information from textual data, it becomes possible to identify and comprehend the sentiments and emotions conveyed. In this end-of-degree work, we analyze and classify the dialogue of characters in an English-language television series as "Rick and Morty" using Python. ... -
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The intellectual system of Eidos
http://lc.kubagro.ru/
http://lc.kubagro.ru/ http://lc.kubagro.ru/aidos/index.htm http://lc.kubagro.ru/aidos/_Aidos-X.htm On the IBM PC, the Eidos system started working in 1992. MS Windows has been running since 2012. Implemented in Alaska+Express. I want to try to translate some modes, and maybe all of them, to the Harbor. The full source text in a single file is here: http://lc.kubagro.ru/__AIDOS-X.txt Responsible Secretary Kubgau scientific journal, Professor of computer science Department Kubgau... -
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OCW Test - Out of Commerce Works
Program for out of commerce works detection
The OCW Test program has been designed to provide assistance in the detection of works outside trade, taking as reference a list of works from a specific bibliographic catalog. In this first version, the program operates on the identifiers of the books of the library of the Complutense University of Madrid. However, the program can be reedited, to work on any bibliographic catalog. -
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apache spark data pipeline osDQ
osDQ dedicated to create apache spark based data pipeline using JSON
This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to... -
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. -
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AXYZ
Newsfeed aggregator
...Among the features of the program, stands out a new processing engine of syndication channels, monitoring capability of information recovery in real time, the possibilities of the configuration of aggregator behavior, automatic classification of contents and new models for representation of information from relational interactive maps. On the other hand, the aggregation program, which named AXYZ, is designed to manage thousands of syndication channels of RSS format. Furthermore it also provides statistics that can be used to study the production of any producer subject and the impact of the information that published in other sources. ... -
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Random Bits Regression
Random Bits Regression is a strong general predictor.
We proposed an accurate, robust and fast general predictor (RBR) for regression and classification in big data era. The application of this method is very broad, from science to industry, finance and health. The accuracy and robustness improvement of our method over existing method could bring huge benefits in some critical applications. For example, natural disaster prediction, stock price prediction, personal/population disease prediction. -
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10
Red-RF
Reduced Random Forest for big data
Red(uced)-RF, a new type of Random Forests that adopts dynamic data reduction and weighted upvoting techniques. Red-RF is favorably applicable to big data: it demonstrates an accurate and efficient performance while achieving a considerable data reduction w.r.t. dataset size. Manuscripts available on IEEE Xplore: H. Mohsen, H. Kurban, K. Zimmer, M. Jenne and M. Dalkilic. Red-RF: Reduced Random Forests using priority voting & dynamic data reduction. In IEEE BigData Congress'2015. H....
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