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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118 views

ExtraTreeClassifier does not handle missing values

I am using sklearn.tree.ExtraTreeClassifier. It does not handle missing value in training data. All tree-based algorithms handle missing value internally. So, is ...
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Multiclass XGBoost train with num classes = 2

I have a tagged csv file with 5 calsses. I accidentally trained am XGBOOST model with this input but forgot to change the num_classes to 5, but instead it was still 2. The model I received seems to ...
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How often do we use m-ary decision trees?

If I come across decision trees, it is a binary tree with predicates internal nodes. How often do we use m-ary decision trees? Is there any combination of m-ary and binary decision tree, e.g. first ...
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143 views

what do the percentages in the leaves of a decision tree represent?

in figure B), there are leaves (gray boxes) with 3 values, for example, the leftmost leaf has 19.3 (28/8.7%) as its values, the 3 values are (19.3, 28, and 8.7%). 19.3 is the average value of the ...
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20 views

How should a decision tree handle an attribute that can be anything?

Say I have AttributeA that can take values A1, A2, A3, AttributeB that can take values B1, B2, B3, etc. and I know ahead of time that my classification table looks like AttributeA | AttributeB | ...
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84 views

Find similarity between 2 sample data points using Random Forest Classifier

Let’s assume that you trained a Random Forest model with 10 estimators on a dataset and passed 2 sample data points (S1 and S2) through each of the trees in the forest. You get to see the leaf node ...
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58 views

Machine Learning Algorithm for 'Performance Rating' to Employees

Which Machine Learning Algorithm should i use for Assigning 'Performance Rating' to each Employee based on his LeaveDaysCount and LeaveExtensionPeriod(If Extended).
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1k views

Why would one use entropy instead of Gini index in CART?

I read this question Gini Impurity vs Entropy and was wondering why would someone use entropy instead of Gini index in a decision tree with scikit-learn. Indeed, I find these arguments legit: ...
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Text classification 'features imput'

I have a text classification task that consists of classifying text into classes (literary genres). I have computed the average word length and sentence length. Also, some POS relative frequency so ...
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1answer
808 views

Value of features is zero in Decision tree Classifier

I used CountVectorizer and TfidfVectorizer seperately to vectorize text which is 100K reviews and passed the vector data to a Decision tree Classifier. Upon using _feature_importances__ attribute of ...
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61 views

When is a neural network better "traditional" models like decisions trees and lassos?

There's a whole theory of statistical inference based off calculus studying consistency, efficiency, robustness, BLUE, unbiasedness of linear models (Gaussian,Exponential, Chi-square, F-distribution, ...
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How important is it for each row of data to have the same number of features?

I'm using decision tree learning to try and classify a device based its components. Different devices have a different number of components and the location of these components within the device is ...
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937 views

Forcing a multi-label multi-class tree-based classifier to make more label predictions per document

I'm been experimenting with tree based classifiers for multi-label document classification. All the trees I've created, however, tend to predict only one or two labels per document. Whereas the ...
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109 views

Does bagging create iid trees?

As the title suggests, I have a question regarding the trees produced through the bagging procedure. Namely, since the bootstrap samples created to fit trees on are independent and identically ...
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53 views

How can I identify the most predictive factors?

I've been playing around with bagged trees and random forests. How can I tell what factors most influenced the categorization? Will scikitlearn just spit it out, or is it trickier than that?
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Random Forest in R: Error in eval(expr, envir, enclos): object not found [closed]

I use the randomForest package in R but I'm getting the following error: ...
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1answer
425 views

Overfitting in machine learning

The graph above shows how accuracy stops increasing after reaching a certain number of features. There are also sudden drops in accuracy at some points. Can this be attrrubuted to overfitting? I am ...
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109 views

Choosing the correct learning algorithm

I am kind of new to the data mining subject but i need help to choose a learning algorithm for my application: The problem: identifying that a certain curve or data set belongs to a certain fault in a ...
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955 views

How to retrieve the clustering results of rpart

I am using rpart package in order to create a segmentation of my data using decision tree. As final result I want to obtain a classification of my data. For exemple, if the rpart devide data into 3 ...
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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 ...
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1answer
22 views

How to build a classification pipeline that will pass to another model?

Not sure if the title explained it, but I am trying to build a pipeline where it's like a decision tree, but also not. Say for example, I had a picture. The model classified the picture, but now I ...
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1answer
53 views

How to identify Overfitting in RandomForestClassifier?

Im building a sentiment classification model using RandomForestClassifier. I got the training accuracy of 99.65 & cross-validation( RepeatedStratifiedKFold-5 folds) accuracy of 97.29. I used f1 ...
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215 views

Getting decision tree like rules for my cluster(s)

After performing clustering and detailed cluster analysis, I am confident that my clusters make sense. Now, for each cluster, I would like to generate rules in the form of decision tree output. With ...
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97 views

Need Advice, Classification Problem in Python: Should I use Decision tree, Random Forests, or Logistic Regression? [closed]

Overview The data set I am working with considers a team that annually plays a 5-game home schedule. My goal is to identify the fans that are most likely to defect for the upcoming season, meaning not ...
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1k views

Space complexity of classification algorithms

There is a categorical dataset consisting of n instances, m attributes. We are performing categorical clustering into K clusters. What is the space complexity for the following classifiers: Decision ...
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708 views

Comparing Categorical and Continuous Features using Splits in GBM

In many GBM models you can get a rough feature importance of a feature by taking the number of splits done on that feature and comparing it to the splits on the other features. This works rather well ...
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42 views

Interpreting MSE in regression Trees

I am using regression tree to predict target variable(continuous). I've use one-hot encoding for all categorical features and applied standard scaler to all numerical features. After all that I train ...
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2answers
2k views

sklearn .fit error

I am trying to copy some code from a video to do a decision tree program, which will predict if a student will pass or not depending on 30 parameters given. I did exactly as written but get an error ...
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66 views

upsampling imbalanced dataset in decision tree

I have a imbalanced dataset with 3 output labels with one class with 98 percent and other two classes with 1 percent each. I need to run decision tree on this dataset. Should i be upsampling this ...
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1answer
113 views

How to train Matlab on a range of IP addresses?

I'd like to train a Decision Tree using the Classification Learner App. I have a range of IP addresses, and a country that the IP address range belongs to. ...
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2k views

Simple Weka classification example in Java gives inconsistent answers

I have the following simple weka code to use a simple decision tree, train it, and then make predictions. ...
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3k views

Master thesis topics [closed]

I am looking for a thesis to complete my master, I am interested in Predictive Analytics in marketing, HR, management or financial subject, using Data Mining Application. I have found a very ...
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6k views

Get values from k-means cluster after clustering

I have a dataset that I have run a K-means algorithm on (scikit-learn), and I want to build a decision tree on each cluster. I can recuperate the values from the cluster, but not the "class" values (I'...

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