Weka / News: Recent posts

Some of you might have come across the python-weka-wrapper3 library, which
makes Weka available from Python:

https://github.com/fracpete/python-weka-wrapper3

When the project started out, it relied on the javabridge library in order to
communicate with Java Virtual Machine running the Weka process. Unfortunately,
that project hasn't been maintained properly for a while now and it made
installation difficult or even impossible for M1/M2 Mac (ARM) users.... read more

Due to the size limitations for repositories on Github, Weka has been moved
in-house again:

https://git.cms.waikato.ac.nz/weka/weka

This repository contains all the branches and all commits, not just a subset
like the Github ones did in the past.

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A new version of WekaDeeplearning4j, version 1.7.0, is available!

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A new version of WekaDeeplearning4j, version 1.6.0, has just been released and
brings with it a bunch of exciting new features.

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A new iteration of More Data Mining with Weka has started and Week 1 is now underway!

Head over to FutureLearn, sign up and get started!

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Users installing Weka on Linux must have always felt left out a bit, with no installer available, instead having to deal with just a ZIP file. For power users, that would not have mattered, but users new to Linux may have found that a bit more challenging.

Well, things have changed - at least for users of Debian or one of its many derivatives like Ubuntu - with the advent of snapshots being available for download as Debian packages (stable 3.8 and developer version).... read more

Users installing Weka on Linux must have always felt left out a bit, with no installer available, instead having to deal with just a ZIP file. For power users, that would not have mattered, but users new to Linux may have found that a bit more challenging.

Well, things have changed - at least for users of Debian or one of its many derivatives like Ubuntu - with the advent of snapshots being available for download as (experimental) Debian packages (stable 3.8 and developer version).... read more

A new iteration of Advanced Data Mining with Weka has started and Week 1 is now underway!

Head over to FutureLearn, sign up and get started!

Read more… (1 min remaining to read)
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In the previous post, I quickly described how to set up Jupyter Notebooks to run Java code. Now I want to explain how to set things up on Windows using Anaconda. Of course, you have to have a Java 9 JDK or later installed on your system, as the JDK's JShell feature is required to execute the Java code on the fly.... read more

Jupyter notebooks are extremely popular in the Python world, simply because it is great to combine documentation and code in a visually appealing way. Makes it an ideal tool for teaching!

A recent post on the MOA blog, demonstrated the IJava kernel for executing Java scripts. The kernel relies on the Java JDK 9+ feature called JShell, which allows executing Java code without compiling it first.... read more

One long-standing annoyance in Weka's user interface was the opening and saving of files: you needed to click many times before you reached your destination. The only thing you were able to modify, for example for the Explorer, was the initial directory a file chooser was using (Explorer.props).... read more

When evaluating multi-class classification models, Weka outputs a weighted average of the per-class precision, recall, and F-measure: it computes these statistics for each class individually, treating the corresponding class as the "positive" class and the union of the other classes as the negative class, and computes a weighted average of these per-class statistics, with a per-class weight that is equal to the proportion of data in that class. A recent question on the Weka mailing list was whether the software also outputs micro-averaged precision, recall, and F-measure for multi-class problems. It turns out that it does! To find out where these can be found, read on.... read more

A frequent question of Weka users is how to implement oversampling or undersampling, which are two common strategies for dealing with imbalanced classes in classification problems. This post provides some explanation.

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Data Mining with Weka and More Data Mining with Weka are underway!

Head over to FutureLearn, sign up and get started!

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Week 1 of Data Mining with Weka is now underway!

Head over to FutureLearn, sign up and get started!

Read more… (1 min remaining to read)
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One role of the Weka software is to provide users with the opportunity to implement machine learning algorithms without having to deal with data import and evaluation issues: when a classifier has been written as a Java class that implements a couple of standard methods defined in the Weka framework, all the goodies that come with Weka are automatically applicable to it, and it will automatically show up in Weka's graphical user interfaces. To see what needs to be done, read on!... read more

New versions of Weka are available for download from the Weka homepage:

• Weka 3.8.3 - stable version

It is available as ZIP, with Win32 installer, Win32 installer incl. JRE 1.8.0_181, Win64 installer, Win64 installer incl. 64 bit JRE 1.8.0_181 and Mac OS X application with Oracle 64 bit JRE 1.8.0_181.

• Weka 3.9.3 - development version

It is available as ZIP, with Win32 installer, Win32 installer incl. JRE 1.8.0_151, Win64 installer, Win64 installer incl. 64 bit JRE 1.8.0_151 and Mac OS X application with Oracle 64 bit JRE 1.8.0_151.... read more

Earlier this year, the company hosting the Weka Wiki made a notice available when logging into the wiki:

Notice
"Over the last twelve months we have been carrying out a complete technical review of the infrastructure and software we use to serve Wikispaces users. As part of the review, it has become apparent that the required investment to bring the infrastructure and code in line with modern standards is very substantial. We have explored all possible options for keeping Wikispaces running but have had to conclude that it is no longer viable to continue to run the service in the long term. So, it is with no small degree of nostalgia, that we will begin to close down later this year."... read more

Kotlin Extensions for Weka

Kotlin is a statically typed programming language for modern multiplatform applications running on the Java Virtual Machine. Its design philosophy is to be a concise and type-safe (e.g. support for non-nullable types) programming language. It supports both object-oriented and functional constructs. Other features include smart casting, operator overloading, higher-order functions, lambdas, and extensions. The latter has led to the formation of a group of Kotlin extension libraries that primarily focuses on the syntactic improvement of other libraries' usages. A key example is Android KTX library, developed by Google, which provides extensions for the Android framework. The purpose of this is to make Android development with Kotlin more concise, pleasant and idiomatic.... read more

In order to make Weka more accessible for people that like having access to the latest code, we have been looking into ways of bringing Weka to Github. Especially, since our faculty already has an organizational account there.

However, Weka was original stored in a CVS repository and then got migrated to Subversion. Not only has it a lot of branches, not all of them are publicly available, like commercial ones. This all complicated the migration to Github.... read more

Week 1 of Advanced Data Mining with Weka is now underway!

Head over to FutureLearn, sign up and get started!

Read more… (1 min remaining to read)
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We are now pleased to announce that the full Data Mining with Weka course is open for enrolment.

http://weka.waikato.ac.nz

The course will start on 9th September and extends over 5 weeks. It features:

· Video lectures
· Practical activities and online assessment
· Extracts from Data Mining (3rd Edition): Witten, Frank & Hall (2011)

You can also follow the course via Twitter or the blog:

https://twitter.com/WekaMOOC... read more

New versions of Weka are available for download from the Weka homepage:

• Weka 3.4.19 - the stable book 2nd edition version available as ZIP, Win32 installer, Win32 installer incl. JRE 1.6.0_21 and Mac OS X application. With the publication of the 3rd edition of the data mining book in January, this will be the last release from the 3.4 code line.

• Weka 3.6.5 - stable book 3rd edition version. It is available as ZIP, with Win32 installer, Win32 installer incl. JRE 1.6.0_21, Win64 installer, Win64 installer incl. 64 bit JRE 1.6.0_21 and Mac OS X application.... read more

The previously announced temporary wiki located at http://weka.wiki.sourceforge.net/ is now the permanent home of the Weka Wiki.

sf.net is currently migrating the old wiki (located at http://weka.wiki.sourceforge.net) to a MediaWiki one. As it is unclear how long the migration process will take, I've setup a temporary wiki over at wikispaces.com.
You can access this wiki at the following location:
http://weka.wikispaces.com/