AutoDiscovery

AutoDiscovery

Butler Scientifics
+
+

Related Products

  • Safetica
    409 Ratings
    Visit Website
  • Criminal IP ASM
    18 Ratings
    Visit Website
  • AthenaHQ
    34 Ratings
    Visit Website
  • JDisc Discovery
    27 Ratings
    Visit Website
  • SciSure
    298 Ratings
    Visit Website
  • DataHub
    10 Ratings
    Visit Website
  • optivalue.ai
    3 Ratings
    Visit Website
  • Digital WarRoom
    55 Ratings
    Visit Website
  • Semarchy xDM
    64 Ratings
    Visit Website
  • AddSearch
    140 Ratings
    Visit Website

About

AutoDiscovery is an intelligent automated exploratory data analysis software that helps biomed researchers unveiling complex relationships hidden in the data files of scientific experiments and clinical trials. AutoDiscovery automatically evaluates the proper statistical tests to assess the relationships between every combination of variables at every individual subset of your data. Cause-effect potential, false discovery rates, small-complex data, groups and treatments and traceability of results are common biomed research needs specifically covered by AutoDiscovery. AutoDiscovery is targeted to Principal Investigators with very little time for data analysis and limited statistical knowledge focused on productive, high impact research.

About

statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration. An extensive list of result statistics is available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open-source Modified BSD (3-clause) license. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. You can also use numpy arrays instead of formulas. The easiest way to install statsmodels is to install it as part of the Anaconda distribution, a cross-platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Businesses searching for an automated data exploration solution

Audience

Users and anyone in search of a solution to calculate the estimation of many different statistical models

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

€1.795 per year
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Butler Scientifics
Founded: 2014
Spain
www.butlerscientifics.com

Company Information

statsmodels
www.statsmodels.org/stable/index.html

Alternatives

CygNet

CygNet

NMSWorks Software

Alternatives

Infrared360

Infrared360

Avada Software
Huawei APM

Huawei APM

Huawei Cloud

Categories

Categories

Data Discovery Features

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

Integrations

Anaconda
Python

Integrations

Anaconda
Python
Claim AutoDiscovery and update features and information
Claim AutoDiscovery and update features and information
Claim statsmodels and update features and information
Claim statsmodels and update features and information