Search Results for "correlation" - Page 2
Sort By:
Showing 32 open source projects for "correlation"
View related business solutions-
Compliant and Reliable File Transfers Backed by Top Security CertificationsStop relying on non-certified, legacy file transfer tools that creak under the weight of modern security demands. Get full audit trails, advanced access controls and more supported by an award-winning team of experts. Start your free 25-day trial today.
-
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
-
1
EZMWeb is an open source web-based bioinformation integration and search system. Users can search the integrated enzyme information.It implements the analysis of correlation between different enzymes,gives its visualized results through java applet.
-
2
This Java native library wraps OpenCV (Computer Vision Lib.) function cvMatchTemplate and implements methods for utilities result visualization. It allows efficient images template matching using Normalized Cross-Correlation (NCC) and others algorithms.
-
3
GoldenOrb is a java library under the Apache License V2.0 for correlation, summarization and clustering of text information.
-
4
NCount is a program that will do a statistical correlation count on a set of points in 1, 2, or 3-dimensions.
-
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
5
-
6
OpenESM project to promote software development of enterprise systems management. Focus areas are (Performance and Availability, Configuration Management, Data Warehousing, Reporting and Correlation).
-
7
Statastizard
Statistics Wizard
...Because time after time, people come to me with some test that they've done that they think "proves" something - when in reality they've either not done a comparative test to start with (ex. a correlation), failed to test for confounding factors (such as normality etc) and as a result, failed to appropriately identify even the right test to do.
