Weka

Java-based Weka (Waikato Environment for Knowledge Analysis) is a well-known machine learning toolkit. A set of machine learning algorithms for data mining applications is called Weka. The algorithms can be called from your own Java code or applied straight to a dataset. Pre-processing, classification, regression, clustering, association rules, and visualization tools are all included in the program. It works well for creating novel machine learning systems as well. The GNU General Public License is used to distribute open-source software like Weka. 

With features for pre-processing data, classifying data, clustering, regression, association rules, and visualization, Weka is a machine learning algorithm for data mining applications.

Pros.

• Free: Available under the GNU General Public License
• Portable: Runs on most modern computing platforms because it's implemented in Java
• User-friendly: Doesn't require programming skills
• Comprehensive: Includes a large number of data mining algorithms, data preprocessing and modeling techniques, and visualization tools

Cons.

• Limited support:  limited literature and online support
• Learning curve: difficult to use without proper guidance and has a learning curve
• File format: File format isn't very popular
• Small datasets: Can only handle small datasets and errors out when a set is larger than a few megabytes
• Outdated techniques
• Become slow after a while

Note: Requires Java Runtime Environment.