Tagged Questions

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0answers
46 views

Variables selection (continuous and classification): how to do in R?

My dataset have both classification (categorical) and continuous variables, ~ 300 variables in all. I'm looking for a way to reduce my attributes to be less than 300 and put them in the decision tree ...
1
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1answer
36 views

How can I calculate leaves and nodes of a C 4.5 decision tree?

I have a given amount of attributes, for example 1024, and now want to calculate the amount of leaves and nodes C 4.5 produces (approximately). Is there something like that for binary trees - a ...
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0answers
61 views

Determining optimal height for regression tree

I have a data set of approximately 400,000 records (for those of you who know, the data set is the one provided by yahoo for their yahoo learning to rank challenge). From this data set I learn a ...
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0answers
358 views

Weka J48 decision tree problem

I have a CSV dataset which contains mean (Numeric), spread (Numeric), review (string), ...
3
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2answers
249 views

Mathematics behind classification and regression trees

Can anyone help explain some of the mathematics behind classification in CART? I'm looking to understand how two main stages happen. For instance I trained a CART classifier on a dataset and used a ...
2
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3answers
280 views

Which type of regression fits better?

I am a newbie in data mining world. I have a general question. I have a data set which has 10 independent variables and one target variable named as category which has 9 values like: 1, 2, 3, 4, 5, 6, ...
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0answers
63 views

Growing a classification tree manually

I want to create some CARTs in R. I used Clementine a while ago for this purpose and remember I could go into "manual mode" and grow the trees by hand. I could manually choose which variable to use ...
2
votes
1answer
162 views

k nearest neighbor with decision tree

A dataset has a few attributes. One of the attributes(attribute X) represents a distance with values expressed in meters. I use cross validation to estimate the performance of Decision tree and k ...
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0answers
36 views

Does the greedy approach only affect pruning?

In ID3, the attributes are split based on Entropy. The attribute and the split value of that attribute that will reduce the Entropy the most are chosen. I understand that the motivation behind this ...
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0answers
184 views

Simulating C4.5 algorithm using Decision Tree node in SAS Enterprise Miner 6.2.

In SAS Enterprise Miner 6.2 it's possible to approximate CHAID and CART methods using Decision Tree node, according to SAS Help, but there is nothing about C4.5 algorithm. How can I mimic C4.5 ...
4
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3answers
609 views

Are decision trees almost always binary trees?

Nearly every decision tree example I've come across happens to be a binary tree. Is this pretty much universal? Do most of the standard algorithms (C4.5, CART, etc.) only support binary trees? From ...
3
votes
1answer
117 views

Use of survival analysis for trigger mining

I am tasked with analyzing data to find "triggers" to an event. Specifically, this is transaction data from a bank (e.g., checking account daily balances, daily over draft fees, daily number of checks ...
2
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2answers
546 views

What are the key statistical concepts that relate to data mining?

What topics in statistics are most useful/relevant to data mining?