Attached you will see one of things requested for the original assignment named (decisiontree) and then second will be the a

Attached you will see one of things requested for the original assignment named (decisiontree) and then second will be the assignment already done that needs to be redone with the notes given by professor. (data mining original)


THESE ARE THE NOTES GIVEN BY PROFESSOR THAT NEED TO BE FIXED

“You needed to use the 1R algorithm for part 2 and use the weather data. Its hard for me to read your work with using X’s and Y’s. I needed to to see each attribute and its calculations (outlook, humidity, windy, temperature )using the 1R algorithm. Once you find the best attribute then you need to draw the final decision tree by hand. For part 3 you need a picture or screen shot of the weather data decision in weka.
I also dont see your j48 tree from the iris dataset and one other algorithm of your choice”




This assignment is in THREE parts!!!  READ ALL


Attached is an example of things requested!!!!


Before you begin: Install Weka data mining package.
(you need to download THIS)  https://www.cs.waikato.ac.nz/ml/weka/  

Weka is a collection of machine learning algorithms for data mining tasks. You will use the Weka software to complete a data mining activity.  
Read on Weka with link below
https://www.cs.auckland.ac.nz/courses/compsci367s1c/tutorials/IntroductionToWeka.pdf

The following is a 23-minute beginner-friendly introduction to data mining with WEKA. The tutorial includes examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine.

https://youtu.be/m7kpIBGEdkI



________________________________________


ASSIGNMENT 

Part 1: Identify iris data set in the installation folder and run J48 algorithm and another algorithm of your choice. Provide a brief (max one page double space) discussion of what you did and your results.

Part 2: Describe a decision tree algorithm based on using the 1R algorithm (Figure 4.1, pg 94 of the textbook) for node splitting. Use your 1R decision tree algorithm to compute a decision tree for the weather data by hand, i.e., at each stage of the computation, use the 1R algorithm to split a node. Show your computations and the resulting tree. Include a picture or scanned image of your hand-drawn tree with your description as part of your assignment file.

Part 3: Use Weka to compute a decision tree for the weather data. Include in the output from your program as part of your assignment file. Provide a brief reflection on how this tree compare with the trees you constructed by hand.


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