Market Basket Analysis and Recommendation Engines
It is actually quite easy to build a market basket analysis or a recommendation engine [1] – if you use KNIME! A typical analysis goal when applying market basket analysis it to produce a set of...
View ArticleReproducibility and KNIME
Obviously advanced analytics starts with an intuitive, yet powerful interface that allows data scientists to quickly explore different ways to blend and analyze their data. Even better, if those...
View ArticleScaling analytics through KNIME
Author: Rohit Agarwal, Fractal Analytics Reposted from Fractal Analytics Blog Post of February 25, 2015http://blog.fractalanalytics.com/advanced-analytics-2/scaling-analytics-through-knime/Fortune 100...
View ArticleSeven Techniques for Data Dimensionality Reduction
The recent explosion of data set size, in number of records and attributes, has triggered the development of a number of big data platforms as well as parallel data analytics algorithms. At the same...
View ArticleGiving the KNIME Server (a) REST
Author: Thorsten Meinl, KNIME.comI guess most of you have heard about web services and many of you will have already used one or more of them. To date there are two main types of web services,...
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Hive execution engine comparison with the KNIME Analytics Platform
This blog describes the usage of the KNIME Analytics Platform to compare the runtime performance of two different Hive execution engines. The heart of an analysis in KNIME is a workflow that consists...
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PMML Integration in KNIME
PMML, the Predictive Model Markup Language, has been around for 18 years now, and has been adopted by many vendors of data mining software. The XML-based format is the de-facto standard for describing...
View ArticleTo Code or not to code – Is that the question?
Many modern data analysis environments allow for code-free creation of advanced analytics workflows. The advantages are obvious: more casual users, who cannot possibly stay on top of the complexity of...
View ArticleKNIME 2.12. The Facts. The Features. New Functionality.
It is here! KNIME 2.12 has just been released on July 31!Access NoSQL databases & JSONWith the new MongoDB Integration, a full suite of dedicated nodes has been made available to access MongoDB....
View ArticleKNIME 3.0 - An Outlook (Part 1)
You have probably already heard the rumors that there will be a KNIME release at the end of September. This is in addition to our usual release cycle of two releases per year, one in July and the other...
View ArticleKNIME in the data-driven lab of the future!
Reproducibility in science is coming under ever growing scrutiny. Datasets are becoming ever more diverse and complex. So doing reproducible science is getting harder, right? Well maybe not. KNIME gets...
View ArticleHow to Setup the Python Extension
With the new Python integration in KNIME you can use an existing Python installation from KNIME. But what if Python is not yet installed on the system? Here is a quick step by step guide on how to...
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KNIME Spring Summit speaker interviews: introducing Benjamin Spiegel of MMI...
Registration for the KNIME Spring Summit 2016 has just opened. To give you a taste of what’s to come, today we are publishing the first of a series of interviews with the speakers invited to present at...
View ArticleAnomaly Detection in Predictive Maintenance with Time Series Analysis
The Newest ChallengeWe are all witnessing the current data explosion: social media data, clinical data, system data, CRM data, web data, and lately tons of sensor data! With the advent of the Internet...
View Article“A New Design” and St. Nicholas!
We at KNIME traditionally schedule releases twice a year – in summer and winter. The winter release is always on December 6. But why? In Germany, December 6 is St. Nicholas Day. On the night before,...
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Sentiment Analysis with N-grams
Sentiment analysis of free-text documents is a common task in the field of text mining. In sentiment analysis predefined sentiment labels, such as "positive" or "negative" are assigned to text...
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KNIME Spring Summit speaker interviews: introducing Stefan Weingaertner of...
The KNIME Spring Summit 2016 in Berlin is only a few weeks away. To give you a taste of what’s to come, today we are publishing the second in our series of interviews with the data scientists invited...
View ArticleThe KNIME Server REST API
The KNIME® Server REST API has already been covered from a design perspective in this blog post by Thorsten. My blog post aims to give you a hands on guide to getting started with the REST API. I’ll...
View ArticleMigrating from Excel to KNIME Analytics Platform
In surveys about the most-used tool for data analysis Excel always comes in as one of the most commonly used tools . It is taught in schools and used by countless companies. What you may not know,...
View ArticleAdvanced Analytics Software’s Most Important Feature? Gartner Says it’s VCF
Thanks to Bob Muenchen (muenchen.bob@gmail.com) for permission to share his post from r4stats.com blog post of February 22, 2016http://r4stats.com/2016/02/22/vcf/That post refers to two graphs here...
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