Search Results for "association"
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Showing 16 open source projects for "association"
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM... -
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NBA Sports Betting Machine Learning
NBA sports betting using machine learning
NBA-Machine-Learning-Sports-Betting is an open-source Python project that applies machine learning techniques to predict outcomes of National Basketball Association games for analytical and betting-related research. The system gathers historical team statistics and game data spanning multiple seasons, beginning with the 2007–2008 NBA season and continuing through the present. Using this dataset, the project constructs matchup features that represent team performance trends and contextual information about each game. ... -
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Weka
Machine learning software to solve data mining problems
Weka is a collection of machine learning algorithms for solving real-world data mining problems. It is written in Java and runs on almost any platform. The algorithms can either be applied directly to a dataset or called from your own Java code. -
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AB3DMOT
Official Python Implementation for "3D Multi-Object Tracking
...The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. This relatively simple design allows the tracker to achieve very high processing speeds while maintaining competitive tracking accuracy. The project also introduces new evaluation metrics specifically designed for assessing performance in 3D tracking benchmarks. The framework has been evaluated on widely used datasets such as KITTI and nuScenes and demonstrates strong performance compared with more complex tracking systems. -
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Pwnagotchi
Deep Reinforcement learning instrumenting bettercap for WiFi pwning
Pwnagotchi is an A2C-based “AI” powered by bettercap and running on a Raspberry Pi Zero W that learns from its surrounding WiFi environment in order to maximize the crackable WPA key material it captures (either through passive sniffing or by performing deauthentication and association attacks). This material is collected on disk as PCAP files containing any form of handshake supported by hashcat, including full and half WPA handshakes as well as PMKIDs. Instead of merely playing Super Mario or Atari games like most reinforcement learning based “AI” (yawn), Pwnagotchi tunes its own parameters over time to get better at pwning WiFi things in the real world environments you expose it to. ... -
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psys
psys is Prolog part of anpe projet
psys is stutent project with prolog to attempt a dialog with machine. This project is part of anpe project. anpe project is Ada neural Prolog engine association project. -
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Chronological Cohesive Units
The experimental source code for the paper
The experimental source code for the paper, "A Novel Recommendation Approach Based on Chronological Cohesive Units in Content Consuming" -
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The Ngram Statistics Package (ngram) is a suite of Perl programs that identifies significant multi word units (collocations) in written text using many different tests of association. NSP/ngram allows a user to add their own tests with minimal effort
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Fingrams Generator
Stand-alone software tool able to generate and visualize fingrams.
...This tool takes as input a standard configuration file easy to be generated from a fuzzy system. Currently, Fingrams can be generated for classification, regression fuzzy rule based systems and fuzzy association rules. GUAJE [http://www.softcomputing.es/guaje], and KEEL [http://www.keel.es] are able to automatically produce the required input file. -
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mwetoolkit
THIS PROJECT MIGRATED TO https://gitlab.com/mwetoolkit/mwetoolkit3/
THIS PROJECT MIGRATED TO https://gitlab.com/mwetoolkit/mwetoolkit3/ The Multiword Expressions toolkit aids in the automatic identification and extraction of multiword units in running text. These include idioms (kick the bucket), noun compounds (cable car), phrasal verbs (take off, give up), etc. Even though it focuses on multiword expresisons, the framework is quite complete and can also be useful in any corpus-based study in computational linguistics. The mwetoolkit can be... -
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yacaree: Yet Another Closure-based Association Rules Experimentation Environment (Development stalled here, check out under Wiki to find where it went.)
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jaf_MT
This implements a phrased-based hidden semi-Markov Model for SMT
This package implements the phrased-based hidden semi-Markov model described: Jesús Andrés-Ferrer, Alfons Juan. A phrase-based hidden semi-Markov approach to machine translation. Procedings of European Association for Machine Translation (EAMT), 2009. pp. 168-175. This project depends on jaf_Utils: http://sourceforge.net/projects/jafutils/ Install it prior installation of jaf_MT. -
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...Double Layered Learning for Biological Event Extraction from Text. In Proceedings of the BioNLP 2011 Workshop Companion Volume for Shared Task, Portland, Oregon, June. Association for Computational Linguistic
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Ferda is a user friendly data mining tool. It is a modular distributed multiplatform framework based on Internet Communications Engine. Ferda is very powerful in working with association rules.
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Wikipedia Concept Association Map (WCAM) is new approach for textual knowledge representation and understanding. All concepts and associations are stored in a graph database for better performance and easy distribution.
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BCAR is a library for the associative classification, which denotes "Boosting Class Association Rules". BCAR provides a general tool for classification tasks with various types of input data.
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