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Downloads:

17,230

Downloads of v 4.6.0:

1,922

Last Update:

16 Jun 2022

Package Maintainer(s):

Software Author(s):

  • KNIME.COM AG

Tags:

knime data analysis analytics statistics data-mining admin

KNIME (Install)

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4.6.0 | Updated: 16 Jun 2022

Downloads:

17,230

Downloads of v 4.6.0:

1,922

Maintainer(s):

Software Author(s):

  • KNIME.COM AG

KNIME (Install) 4.6.0

Legal Disclaimer: Neither this package nor Chocolatey Software, Inc. are affiliated with or endorsed by KNIME.COM AG. The inclusion of KNIME.COM AG trademark(s), if any, upon this webpage is solely to identify KNIME.COM AG goods or services and not for commercial purposes.

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Some Checks Have Failed or Are Not Yet Complete

Not All Tests Have Passed


Validation Testing Passed


Verification Testing Failed

Details

Scan Testing Successful:

No detections found in any package files

Details
Learn More

Deployment Method: Individual Install, Upgrade, & Uninstall

To install KNIME (Install), run the following command from the command line or from PowerShell:

>

To upgrade KNIME (Install), run the following command from the command line or from PowerShell:

>

To uninstall KNIME (Install), run the following command from the command line or from PowerShell:

>

Deployment Method:

NOTE

This applies to both open source and commercial editions of Chocolatey.

1. Enter Your Internal Repository Url

(this should look similar to https://community.chocolatey.org/api/v2/)


2. Setup Your Environment

1. Ensure you are set for organizational deployment

Please see the organizational deployment guide

2. Get the package into your environment

  • Open Source or Commercial:
    • Proxy Repository - Create a proxy nuget repository on Nexus, Artifactory Pro, or a proxy Chocolatey repository on ProGet. Point your upstream to https://community.chocolatey.org/api/v2/. Packages cache on first access automatically. Make sure your choco clients are using your proxy repository as a source and NOT the default community repository. See source command for more information.
    • You can also just download the package and push it to a repository Download

3. Copy Your Script

choco upgrade knime.install -y --source="'INTERNAL REPO URL'" [other options]

See options you can pass to upgrade.

See best practices for scripting.

Add this to a PowerShell script or use a Batch script with tools and in places where you are calling directly to Chocolatey. If you are integrating, keep in mind enhanced exit codes.

If you do use a PowerShell script, use the following to ensure bad exit codes are shown as failures:


choco upgrade knime.install -y --source="'INTERNAL REPO URL'" 
$exitCode = $LASTEXITCODE

Write-Verbose "Exit code was $exitCode"
$validExitCodes = @(0, 1605, 1614, 1641, 3010)
if ($validExitCodes -contains $exitCode) {
  Exit 0
}

Exit $exitCode

- name: Install knime.install
  win_chocolatey:
    name: knime.install
    version: '4.6.0'
    source: INTERNAL REPO URL
    state: present

See docs at https://docs.ansible.com/ansible/latest/modules/win_chocolatey_module.html.


chocolatey_package 'knime.install' do
  action    :install
  source   'INTERNAL REPO URL'
  version  '4.6.0'
end

See docs at https://docs.chef.io/resource_chocolatey_package.html.


cChocoPackageInstaller knime.install
{
    Name     = "knime.install"
    Version  = "4.6.0"
    Source   = "INTERNAL REPO URL"
}

Requires cChoco DSC Resource. See docs at https://github.com/chocolatey/cChoco.


package { 'knime.install':
  ensure   => '4.6.0',
  provider => 'chocolatey',
  source   => 'INTERNAL REPO URL',
}

Requires Puppet Chocolatey Provider module. See docs at https://forge.puppet.com/puppetlabs/chocolatey.


4. If applicable - Chocolatey configuration/installation

See infrastructure management matrix for Chocolatey configuration elements and examples.

NOTE

Private CDN cached downloads available for licensed customers. Never experience 404 breakages again! Learn more...

NOTE

This package is likely a meta/virtual (*) or an installer (*.install) or portable (*.portable) application package.

  • Meta/virtual (*) - has a dependency on the *.install or the *.portable package - it is provided for discoverability and for other packages to take a dependency on.
  • Portable (*.portable/*.commandline (deprecated naming convention)/*.tool (deprecated naming convention)) - usually zips or archives that require no administrative access to install.
  • Install (*.install/*.app (deprecated naming convention)) - uses native installers, usually requires administrative access to install.

Learn more about chocolatey's distinction of installed versus portable apps and/or learn about this kind of package.

Package Approved

This package was approved as a trusted package on 16 Jun 2022.

Description

KNIME Analytics Platform

KNIME Analytics Platform is the open source software for creating data science applications and services. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone.

Build end to end data science workflows

Create visual workflows with an intuitive, drag and drop style graphical interface, without the need for coding.

Blend tools from different domains with KNIME native nodes in a single workflow, including scripting in R & Python, machine learning, or connectors to Apache Spark.

Choose from over 2000 modules ("nodes") to build your workflow. Model each step of your analysis, control the flow of data, and ensure your work is always current.

Get up and running quickly. Select one of the hundreds of publicly available example workflows, or use the integrated workflow coach to guide you through building your workflow.

Blend data from any source

Open and combine simple text formats (CSV, PDF, XLS, JSON, XML, etc), unstructured data types (images, documents, networks, molecules, etc), or time series data.

Connect to a host of databases and data warehouses to integrate data from Oracle, Microsoft SQL, Apache Hive, and more. Load Avro, Parquet, or ORC files from HDFS, S3, or Azure.

Access and retrieve data from sources such as Twitter, AWS S3, Google Sheets, and Azure.

Shape your data

Derive statistics, including mean, quantiles, and standard deviation, or apply statistical tests to validate a hypothesis. Integrate dimension reduction, correlation analysis, and more into your workflows.

Aggregate, sort, filter, and join data either on your local machine, in-database, or in distributed big data environments.

Clean data through normalization, data type conversion, and missing value handling. Detect out of range values with outlier and anomaly detection algorithms.

Extract and select features (or construct new ones) to prepare your dataset for machine learning. Manipulate text, apply formulas on numerical data, and apply rules to filter out or mark samples.

Leverage Machine Learning and AI

Build machine learning models for classification, regression, dimension reduction, or clustering, using advanced algorithms including deep learning, tree-based methods, and logistic regression.

Optimize model performance with hyperparameter optimization, boosting, bagging, stacking, or building complex ensembles.

Validate models by applying performance metrics including Accuracy, R², AUC, and ROC. Perform cross validation to guarantee model stability.

Make predictions using validated models directly, or with industry leading PMML, including on Apache Spark.

Discover and share insights

Visualize data with classic (bar chart, scatter plot) as well as advanced charts (parallel coordinates, sunburst, network graph) and customize them to your needs.

Display summary statistics about columns in a KNIME table and filter out anything that’s irrelevant.

Export reports as PDF, Powerpoint, or other formats for presenting results to stakeholders.

Store processed data or analytics results in many common file formats or databases.

Scale execution with demands

Build workflow prototypes to ​explore various analysis approaches. Inspect and save intermediate results to ensure fast feedback and efficient discovery of new, creative solutions.

Scale workflow performance through in-memory streaming and multi threaded data processing.

Exercise the power ​of in-database processing or distributed computing on Apache Spark to further increase computation performance.

KNIME License Terms and Conditions

Please see the GPL v3, and the Additional Permissions according to Sec. 7


tools\chocolateyInstall.ps1
$ErrorActionPreference = 'Stop'

$packageArgs = @{
  packageName    = 'knime.install'
  fileType       = 'exe'
  url64bit       = 'https://download.knime.org/analytics-platform/win/KNIME%204.6.0%20Installer%20%2864bit%29.exe'
  checksum64     = '4a4d668afa7461cc0e62164d2408647f1dd6b39cdbd594e290fd8bc460be8a8a'
  checksumType64 = 'sha256'
  silentArgs     = '/VERYSILENT /SUPPRESSMSGBOXES /NORESTART /SP-'
  validExitCodes = @(0)
}
Install-ChocolateyPackage @packageArgs

Log in or click on link to see number of positives.

In cases where actual malware is found, the packages are subject to removal. Software sometimes has false positives. Moderators do not necessarily validate the safety of the underlying software, only that a package retrieves software from the official distribution point and/or validate embedded software against official distribution point (where distribution rights allow redistribution).

Chocolatey Pro provides runtime protection from possible malware.

Add to Builder Version Downloads Last Updated Status
KNIME (Install) 4.5.2 422 Wednesday, March 23, 2022 Exempted
KNIME (Install) 4.5.1 363 Friday, January 21, 2022 Approved
KNIME (Install) 4.5.0 343 Monday, December 6, 2021 Approved
KNIME (Install) 4.4.2 279 Thursday, October 21, 2021 Exempted
KNIME (Install) 4.4.1 328 Wednesday, August 25, 2021 Exempted
KNIME (Install) 4.4.0 366 Wednesday, June 30, 2021 Approved
KNIME (Install) 4.3.3 237 Saturday, June 12, 2021 Approved
KNIME (Install) 4.3.1 468 Friday, January 29, 2021 Approved
KNIME (Install) 4.3.0 317 Sunday, December 6, 2020 Approved
KNIME (Install) 4.2.3 255 Wednesday, November 4, 2020 Approved
KNIME (Install) 4.2.2 294 Monday, September 28, 2020 Approved
KNIME (Install) 4.2.1 244 Wednesday, August 26, 2020 Approved
KNIME (Install) 4.2.0 323 Thursday, August 13, 2020 Approved
KNIME (Install) 4.1.3 398 Wednesday, May 13, 2020 Approved
KNIME (Install) 4.1.2 395 Thursday, March 5, 2020 Approved
KNIME (Install) 4.1.1 308 Wednesday, February 5, 2020 Approved
KNIME (Install) 4.1.0 369 Friday, December 6, 2019 Approved
KNIME (Install) 4.0.2 364 Tuesday, October 1, 2019 Approved
KNIME (Install) 4.0.1 647 Thursday, August 15, 2019 Approved
KNIME (Install) 4.0.0 520 Thursday, June 27, 2019 Approved
KNIME (Install) 3.7.2 317 Thursday, April 18, 2019 Approved
KNIME (Install) 3.7.1 579 Saturday, February 2, 2019 Approved
KNIME (Install) 3.7.0 324 Saturday, January 19, 2019 Approved
KNIME (Install) 3.6.2 422 Tuesday, November 6, 2018 Approved
KNIME (Install) 3.6.1 666 Sunday, September 9, 2018 Approved
KNIME (Install) 3.6.0 408 Wednesday, July 18, 2018 Approved
KNIME (Install) 3.5.2 465 Tuesday, February 6, 2018 Approved
KNIME (Install) 3.5.1 452 Wednesday, January 3, 2018 Approved
KNIME (Install) 3.5.0 416 Wednesday, December 6, 2017 Approved
KNIME (Install) 3.4.2 413 Tuesday, November 14, 2017 Approved
KNIME (Install) 3.4.1 368 Monday, October 30, 2017 Approved
KNIME (Install) 3.4.0 448 Thursday, July 13, 2017 Approved
KNIME (Install) 3.3.2 471 Saturday, April 8, 2017 Approved
KNIME (Install) 3.3.1 480 Monday, January 16, 2017 Approved
KNIME (Install) 3.2.1 549 Thursday, September 22, 2016 Approved
KNIME (Install) 3.1.2 457 Sunday, April 10, 2016 Approved
KNIME (Install) 3.1.1 434 Saturday, February 13, 2016 Approved
KNIME (Install) 3.1 399 Friday, January 15, 2016 Approved

This package has no dependencies.

Discussion for the KNIME (Install) Package

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  • This discussion is only about KNIME (Install) and the KNIME (Install) package. If you have feedback for Chocolatey, please contact the Google Group.
  • This discussion will carry over multiple versions. If you have a comment about a particular version, please note that in your comments.
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  • Tell us what you love about the package or KNIME (Install), or tell us what needs improvement.
  • Share your experiences with the package, or extra configuration or gotchas that you've found.
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