Search Results for "weka mac"
Sort By:
Showing 7 open source projects for "weka mac"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
It gives facility of collecting tweets through Twitter Streaming API w.r.t different search criteria and to save tweets in CSV and ARFF (WEKA) file formats.
-
2
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.
-
3
Open data mining platform. Provides common architecture for algorithms of various types. Efficient processing of arbitrarily large volumes of data thanks to data streaming. Weka and Rseslib partially integrated. (www.debellor.org)
-
4
Genetic Programming (tree structure) predictor within Weka data mining software for both continuous and classification problems.
-
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
5
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.
-
6
Weka-Parallel is a modification to Weka, created with the intention of being able to harness the power of Weka and the speed of parallel processing to be able to run a number of data mining and machine learning algorithms quickly.
-
7
Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
- Previous
- You're on page 1
- Next
