I am using weka to analyse data sets using id3 and j48 trees. However, the id3 classification doesn't allow you to graphically see the tree. Can the pruning for the j48 tree be turned off to obtain an id3?
From the Weka Javadoc
Valid options are:
-U
Use unpruned tree.
So I think that answers your question.
Related
I am a phd student in data mining and i want to use constraint programming to solve pattern mining tasks,
Knowing that constraint programming is based on a tree search, i would like to know if there is a common way to represent the data of a numerical dataset on a tree search.
I have only found discrete data represented in a CP tree search:
Example of discrete data representation in a CP tree search:
Discrete dataset:
Corresponding tree representation:
So supposing we have the following numerical dataset:
How can i represent the numerical values (data) into a cp tree search without discretizing my dataset ?
I had an excel sheet i converted it to ARFF file using online facility, but when i tried to open it in the 3.8 version of WEKA software it is showing me this error--
I have attached the image of the dialog box which is popping. Please help me out.
Thanks in advance
You can just open the CSV file with Weka explorer and save it as arff you really need it in that format.
EDIT:
Your problem is not the file format. It seems that all of your values are numeric. J48 is a classification algorithm and therefore Weka won't let you use it on numeric data.
Which column in the data is the target?
IF you want to use classification algorithm, you need to do one of the following: use a numeric-to-nominal filter on the target feature, use an arff file where you specify that the target column is nominal or rename the values of the column to non-numeric values. Here is a link to an arff file where the last column (race) is defined as nominal: https://drive.google.com/open?id=0B7b0iysQV1SEcjJJUE1lc19fR2c
I want to find the similarity using cosine similarity operator on the structured dataset but I am not getting the desired result. Can someone guide me how to find the similarity using the Rapidminer?
Sample dataset:
I am using Weka for Data mining a dataset. I can find median, stdev using explorer but not range, quartiles, variance and mode. Is there any configuration required in the tool for the same or it just can't possible with the tool?
You can use a Filter, the Unsupervised Attribute Filter "AddExpression" or the "MathExpression", to calculate something for a single attribute.
Obviously, this is primitive, and you cannot do this for each attribute in one fell swoop.
Hi My dataset contains only quantitative data(numerical). It doesn't have any class attributes. The dataset contains with sales of different years. I need to analyze the data in different ways. Can I use WEKA for this analysis? I tried to use WEKA tool. But it seemed I cannot proceed with WKA unless I have class variables for the dataset. Please kindly give me a hint.