Questions tagged [decision-trees]

A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm.

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12
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3answers
19k views

Unbalanced classes -- How to minimize false negatives?

I have a dataset that has a binary class attribute. There are 623 instances with class +1 (cancer positive) and 101,671 instances with class -1 (cancer negative). I've tried various algorithms (Naive ...
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1answer
11k views

What is a benchmark model?

I am working on a breast cancer dataset (http://kdd.org/kdd-cup/view/kdd-cup-2008). I need to perform classification on the data using C4.5 algorithm, after doing any necessary pre-processing. A ...
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2answers
7k views

How is cross validation used to prune a decision tree

As I understand it one can use cross validation to help find the optimal pruning of a classification or regression tree, for example, implemented here in Matlab. I do not understand the following ...
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1answer
706 views

Pick a model from multiple models using a decision tree

Let us say, I have 4 classification models on a training data set of various examples. Now, I want to choose which 1 out 4 models (or what combination of the 4 ...
3
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1answer
3k views

Extract the "path" of a data point through a decision tree in sklearn

I'm working with decision trees in python's scikit learn. Unlike many use cases for this, I'm not so much interested in the accuracy of the classifier at this point so much as I am extracting the ...
1
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1answer
674 views

How to choose the order in which to split a decision tree?

I know that a decision tree recursively splits along each attribute, greedily minimizing the wrong classifications/deviance at each split. But, what is the order in which the attributes are split? ...
23
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3answers
76k views

How to predict probabilities in xgboost using R?

The below predict function is giving -ve values as well so it cannot be probabilities. ...
1
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0answers
199 views

How to build a unique decision tree for each subset of data based on a grouping variable?

Given: a data frame of 2.5 million records and 25 columns, which contains 1 grouping column with a variable number of groups (e.g. 2.5M records / 10 groups today; 2.5M records / 50 groups tomorrow). ...
0
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0answers
1k views

Entropy calculation for MNIST dataset to form classification decision tree

I am trying to get classification tree in R. I am using MNIST (handwritten digit dataset) to train my decision tree. The dataset has 28*28 pixel box. Pixels are organized in row-wise. Pixel values are ...
29
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5answers
46k views

Are decision tree algorithms linear or nonlinear

Recently a friend of mine was asked whether decision tree algorithms are linear or nonlinear algorithms in an interview. I tried to look for answers to this question but couldn't find any satisfactory ...
4
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3answers
4k views

How to explain decision tree algortihm in layman's terms?

I have a task at hand, where I have to explain decision tree algorithm to a person who has not much understanding of ...
7
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1answer
11k views

How to preprocess different kinds of data (continuous, discrete, categorical) before Decision Tree learning

I want to use some Decision Tree learning, such as the Random Forest classifier. I have data of different types: continuous, discrete and categorical. How do I have to preprocess data in order to ...
0
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1answer
170 views

Weka class attribute suggestion

We are trying to run J48 on a classified data set. Our class attribute has two possible values ( 0,1) when running J48 the tree terminates at the very first node and doesnt process any further. ...
0
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1answer
979 views

Cross validation for C5.0 algorithm

I want to try K-fold cross validation in R for C5.0 algorithm, The following is the code i use. Can someone suggest me how can i include k-fold as well? Classifi_C5.0 <- C5.0(TARGET ~., , data = ...
3
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1answer
2k views

Over-fitting issue in a classification problem (unbalanced data)

I am working on a rare event (unbalanced target variable) classification problem using decision trees. My dataset comprises of 95% non-event and 5% minority (events) class. I used decision tree over ...
16
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4answers
46k views

Should I use a decision tree or logistic regression for classification?

I am working on a classification problem. I have a dataset containing equal numbers of categorical variables and continuous variables. How do I decide which technique to use, between a decision tree ...
2
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1answer
283 views

Question on decision tree in the book Programming Collective Intelligence

I'm currently studying Chapter 7 ("Modeling with Decision Trees") of the book "Programming Collective intelligence". I find the output of the function mdclassify()...
1
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1answer
640 views

Does pruning a decision tree always make it more general?

If I prune a decision tree, does that make the resulting decision tree always more general than the original decision tree? Are there examples where this is not the case?
82
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6answers
124k views

strings as features in decision tree/random forest

I am doing some problems on an application of decision tree/random forest. I am trying to fit a problem which has numbers as well as strings (such as country name) as features. Now the library, scikit-...
1
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0answers
170 views

Decision Tree Bayes rules / Maximax / Maximin

I need to draw a decision tree about this subject : The research and development manager in an old oil company, which is considering making some changes, lists the following courses of action ...
4
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2answers
248 views

Distributed Scalable Decision Trees

Are there any good sources that explain how decision trees can be implemented in a scalable way on a distributed computing system. Where in a given source is this explained?

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