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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21 views

Decision Trees Should We Discard Low Importance Features?

I just started to work with feature selection. Let's say I have a decision tree model. I get its feature importances by tree.feature_importances_. In my model out ...
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How to know if my Decision tree model is good or bad?

I have built a decision tree model. I am not sure if it is good or bad as i am new comer in ML. Kindly help to evaluate my model" Here is my code which i used, ...
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Calculate future GDP % using machine learning

I need to estimate the GDP % of a country three years into the future, based on historic data. I have 30+ years of the following monthly data that includes features such as inflation and unemployment ...
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37 views

Decision tree classifier prediction changes from one run of the model to the next

I'm running a very basic gender ['male', 'female'] classifier using the sklearn DecisionTreeClassifier based on ...
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Decision Trees - how does split for categorical features happen?

A decision tree, while performing recursive binary splitting, selects an independent variable (say $X_j$) and a threshold (say $t$) such that the predictor space is split into regions {$X|X_j < t$} ...
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clarification on splitting individual trees in extra trees?

So I am a beginner in machine learning and just started learning about random trees in this article here. When it talks about tuning the hyperparameter K, I'm a bit confused as to how it works. It ...
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21 views

CART algorithm (Classification and regression trees) question

So this is taken from an exam I just did. I'd like to know if there are any instances same as in the image where the CART algorithm could use a negative alpha and thus encourage a larger tree? Or does ...
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18 views

when to use certain metrics for splitting decision trees?

So I just very recently learned about decision trees, and the different metrics for determining the best split when training the tree. I cannot seem to be able to find anything on which metric to use ...
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11 views

Gradient Boosting Partial Dependency Plot

I have been trying to generate a partial development plot using gradient boosting. The Plot looks like as below. My question is why the plot shows two or three steps rather than several broken ...
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How to interpret fit from regression (decision) tree which has used 0 variables

I have fit a regression tree to my dataset and the output from summary(tree1) is as follows: ...
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30 views

How does class_weight work in Decision Tree

The scikit-learn implementation of DecisionTreeClassifier has a parameter as class_weight. ...
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59 views

How does Decision Tree with Gini Impurity Calculate Root Node?

I couldn't figure out how it selected the root node with with <=7.5 and it's gini impurity is 0.45 but I tried to manually ...
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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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Can we use DecisionTreeClassifier of sklearn for continuous target variable?

I have a continuous target variable named "quality" which ranges from 0 to 10. Also I have 11 input variables in my dataset. When I'm building my model using DecisionTreeClassifier() of sklearn then ...
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Is it possible to ensure that all classes are represented in the output of a scikit-learn decision tree?

I am working with an ordinal classification problem with six ordered classes and I want to compare a neural network classifier with a baseline classifier that is as simple and parameter-free as ...
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28 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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Unexpected results from scikit learn regression decision tree

Apologies for this newbie question. I have a scikit learn DecisionTreeRegressor with muti-variable output. If the output is in the format [ output_var1, ...
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1answer
94 views

Number of Nodes in Isolation Forest

I am currently reading this paper on Isolation Forest. At page 3, there is a definition of Isolation Tree and there are a couple of sentences that I don't understand: Given a sample of data X = {...
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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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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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“DeepTree” network with binary classifiers at each node

I need to do a project where I build a "DeepTree Network". Let's say I have a 3-classification problem with classes A, B, and C. My tree should then look like this: first node: ...
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20 views

How to optimise a boolean expression

I am working on an optimization problem involving Boolean expressions and wanted some help as I have very little knowledge about the topic. The problem statement is as follows: There are a set of ...
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49 views

Classify samples based on other sample probabilities

I was wondering if there's a way to train a classifier or set up a way of classifying after that can classify certain samples as some relationship between the previous two. I notice that, for example,...
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15 views

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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27 views

Random Forest Classifier: Find the decision path for a single data point

I am working with RandomForestClassifier and I would like to be able to analyse the decision path which each decision tree takes for a single data point. What I understand is that the final prediction ...
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1answer
42 views

Hand-crafted decision tree inspired from learned decision tree

Goal of this question: As I am the only 'machine learning guy' in our group, I wanted to get an outsiders view, that is a sanity check if what I am doing adheres at least to 'decent practices' in ...
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42 views

TDIDT Decision Trees algorithm

What is the Difference between TDIDT, ID3, CART, and C4.5? My main concern is about TDIDT, Is it first ever algorithm that came with Decision trees? Is it predecessor or successor of ID3, CART, ...
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Is there a term for measuring error on a second prediction based on the first's?

I have created a dataset which contains six values per row which may be the target value. Two rows for example: ...
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Removing ambiguous data: Same input variables with different class labels

Background: I'm working with a tree-based ensemble model on a large data set. The target variable y is a binary attribute that have two classes (True and False). I noticed that some of the ...
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260 views

Why decision tree needs categorical variable to be encoded?

As per my intuition, decision trees should work better with categorical variables than with continuous variables. If this is the case, why is encoding needed on categorical variables? Can someone give ...
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136 views

is it possible to output more than 2 nodes away from a node in a decision tree? if yes, how to do that with sklearn?

usually a decision tree has one root node, some nodes, and some leaves. lots tutorial illustrate this as something like binary tree. is it possible more than 2 nodes away from a node in a decision ...
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1answer
18 views

Decision Tree Optimize Deviation From Objective

I have the following problem: I have three classes/modes, let's call them car, bike, and walking. For any given test data instance with some environmental variables such as distance, road quality etc, ...
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59 views

Does feature selections matter to Decision Tree algorithms?

Background: Currently I'm working with my thesis project, which is to build a Tree-based ensemble methods for classification on a large data set. Before I started with modelling, I've spent a large ...
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14 views

Drawing Trees, finding Probabilities and Predicting

My first post here :) I have some transition states. Like below, where each row reflect to a specific process: ...
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12 views

Why do we negate entropy in decision trees

\begin{equation} i(N) = - \sum_{j=1}^{c} P_jlogP_j \end{equation} Why don't we calculate Impurity simply without negation and then decide descendent node variable on minimum impurity based?
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How can I get 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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2answers
222 views

Why is random forest an improvement of decision tree?

Let's assume that we have a binary classification problem, and we built a decision tree on our data set. Assuming that we have 5 features, then the decision tree, in the first step, will choose the ...
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115 views

What is the best algorithm/solution for predicting the following?

I have a dataset that comprises 76 countries, and 6 columns of distinct quantitative variables, which are the mean values of that variable relative to each country: If I were to take a random sample ...
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1answer
80 views

Keras: How to connect a CNN model with a decision tree

I want to train a model to predict one's emotion from the physical signals. I have a physical signal and using it as input feature; ecg(Electrocardiography) I want to use the CNN architecture to ...
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40 views

Why is not AUC or other metrics used for splitting nodes in decision trees?

There are common ways to split a tree in decision trees and all their variants: Gini Index Entropy Misclassification Why there is not a method which uses directly AUC or accuracy (or whichever the ...
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18 views

UnderBagging Testing in Matlab

I used UnderBagging for an imbalanced dataset with 45700 observation with 20 fetures. 45000 observations are 1 and 700 are 0. I used UnderBagging for classifier C ( for example for Decision Tree). I ...
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Will the combination of Chaid/CART tree modelling improve the accuracy of the Decision Tree Regression Model?

Will the performance of the decision tree regression model significanlty improve if we consider CHAID modelling first by identifying the key continous/categorical dependent variables and then builidng ...
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1answer
130 views

Isolation Forest Score Function Theory

I am currently reading this paper on isolation forests. In the section about the score function, they mention the following. For context, $h(x)$ is definded as the path length of a data point ...
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6 views

Confidence vs. Count in association rule mining: which one is better?

I am writing a program that mines association rules from a large data set. I have an array of association rules, and I have to decide which ones are more representative of the patterns I am studying. ...
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33 views

Training xgboost model with more data having different characteristic

I have trained my model for ECG data which has 8528 ECG files having length 30s and sample rate 300 so total file length in csv ...
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1answer
36 views

Decision trees With branching Factor?

How to construct a Binary Tree from a decision tree with branching factor greater than 2 (b>2)?
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201 views

Categorical Variables in Decision Tree

I was going through the Andrew Ng's notes for Decision Trees. It has one section explaining the usage of categorical variables using Decision Trees in which I am not able to understand this part " A ...
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1answer
49 views

What happens to a machine learning technique (specifically Decision Tress and Logistic Regression) if the validation dataset has a new category?

Let's suppose I have a dataset which has a categorical variable and the problem I am solving is a classification one. This categorical variable var has ['A','B','C'] as the possible set of data. ...
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38 views

RandomForestRegressor intermittantly returning a single prediction

BACKGROUND I have a RandomForestRegressor from scikit-learn which, for each example row, takes in four float features and ...