It depends on the datasets and algorithms you want to use. Weka does not incorporate all the algorithms, so python is required in some cases. You may use orange, rapidminer, keel as well.

Weka is fast, python and R are flexible.

R studio (https://www.rstudio.com/) for desktop, and r shiny (https://shiny.rstudio.com/) for interactive analysis or python libraries (it depends on what exactly you want to do with your data) , see also ploty available on both python and R (https://plot.ly/).

Hello,

I use RStudio and I am very satisfied.

Rstudio is Best

It depends on the datasets and algorithms you want to use. Weka does not incorporate all the algorithms, so python is required in some cases. You may use orange, rapidminer, keel as well.

I recommend Python or R and Jupyter Lab (Jupyter Notebook)

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

I recommend Weka, R, Python and KEEL (http://www.keel.es/).

R, Python and Azure can support different algorithms.

Most of the cases I used WEKA and gave good result. R is also very good and provide more flexibility and features.

I use Orange and KNIME. The KNIME server is rich with useful resources. R is a flexible alternative and Weka is also a good platform depending on the nature of the dataset and the algorithm you prefer.

Nowaday, we must thing in big, i recooment for you study some Big data tools, such as: Apache Spark, Kafka, Flink, Storm and others. Maily Apache Spark that is a good bigdata engine that includes MLlib(current version only ML), ML is Machine learning library. This library includes Linear and logistic regresion, Classification based on SVM, neural networks, desition trees and other very useful for educational datamining and based on MapReduce paradigm.

R programming & Weka@

As Sadiq Hussain said, it depends on the type of analysis you want to do and on the nature of your data, however, I would recommend SPFM: an open-source data mining mining library written in Java, specialized in pattern mining. It offers implementations of 171 data mining algorithms. The source code of each algorithm can be easily integrated in other Java software. Moreover, SPMF can be used as a standalone program with a simple user interface or from the command line.

I use KNIME or ORANGE

i think the wake is best because easy to used and easy to experiments.