Search Results for "java machine learning library" - Page 2
Sort By:
Showing 31 open source projects for "java machine learning library"
View related business solutions-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
1
jStates is a java library for easy state machine design and implementation.It uses XML to define states and state transitions. jStates is aimed at easy integration with desktop J2SE applications, Struts, Commons Validator, Web and other J2EE technologies
-
2
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.
-
3
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/.
-
4
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.
-
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
5
The OS561 operating system based around FORTH/Java. The OS is to run on a VHDL chip OpenHardware design called the Minon, but could become available for other platforms. The unique point of the design is a revolutionary data compression technology.
-
6
Takthons provides container and manipulation services for evolved machine language routines. This allows the calling application to concentrate on the UI, the fitness evaluation and the genetic operations rather than the machine language details.
