Dear all,
I want to work on decision tree classification, please suggest me which is the best software..?.
And from were I can download the Agro-climate zone map of Asia. If some one wants to share Agro-climate zone map(raster/vector), I will acknowledge the valuable contribution in my thesis.
My email Id: [email protected]
I will be thankful for your valuable response.
Regards
Dear Prashant Patil,
several tools are available to make classification with decision trees. In my opinion, the most common and easy-to-use tools are the following three:
This is a freely available data mining software. A lot of classification models can be easily learned with Weka, including decision trees. See the first attached link.
Another software for data mining. With KNIME you can construct an analytic flow with data processing and cleaning, classification or clustering, validation, etc. Decision trees are implemented in this software. Please see the second attached link.
If you can program, the best solution is to use the scikit-learn package provided by Python, which provides the most flexible way to perform data mining experiments. All the main classification models are implemented in scikit-learn, including decision trees. See the third attached link.
Best regards,
Luca
http://www.cs.waikato.ac.nz/ml/weka/
https://www.knime.org/
http://scikit-learn.org/
Dear Prashant Patil,
several tools are available to make classification with decision trees. In my opinion, the most common and easy-to-use tools are the following three:
This is a freely available data mining software. A lot of classification models can be easily learned with Weka, including decision trees. See the first attached link.
Another software for data mining. With KNIME you can construct an analytic flow with data processing and cleaning, classification or clustering, validation, etc. Decision trees are implemented in this software. Please see the second attached link.
If you can program, the best solution is to use the scikit-learn package provided by Python, which provides the most flexible way to perform data mining experiments. All the main classification models are implemented in scikit-learn, including decision trees. See the third attached link.
Best regards,
Luca
http://www.cs.waikato.ac.nz/ml/weka/
https://www.knime.org/
http://scikit-learn.org/
As Luca recommended, Weka is good choice, particularly if you are a Java programmer.
You can also try the packages for decision tree learning avaliable for R, such as C5.0 (an extension of the famous C4.5 algorithm):
https://cran.r-project.org/web/packages/C50/C50.pdf
see also: http://www.rdatamining.com/examples/decision-tree
Dear Dr. Luca and Eduardo,
Thank you for you both of them for your valuable suggestions and kind information's. I will go through your provided suggestions and try to do choose best tool and get some good valuable outputs.
Regards-PTP
Hi there Prashant,
My experience with ENVI is perfect. To download go to: http://envi.software.informer.com/4.3/
Success,
Frank
Dear Dr. Frank,
Thank you very much for your valuable suggestion. I tried with ENVI on small area and what I came to know is using ENVI is best option to get quick output, easy to understand and construction of decision tree for classification.
Regards-PTP
You can check the SpiceLogic Decision Tree software, https://www.spicelogic.com/Products/decision-tree-software-27. Not only it is good for Rational Decision Making with Normative Decision Theories, but also it comes with a feature for generating a decision tree from data like CSV, Excel and SQL Server. It uses a mix of ID3 and C4.5 Algorithms. It can generate a classification decision tree and regression trees. Here is a video. https://youtu.be/SlfNFAXYahs
As of today, it has some limitations though. For example:
- It does not handle missing data well.
- it may not behave well with ill-formatted data.
- It won't allow you to set any specific algorithm or it won't let you fine-tuning algorithms with parameters.
Missing features:
- It does not show a confusion matrix by validating against test data.
I have attached some screenshots for your convenience.
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