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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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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18 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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“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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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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1answer
19 views

Random forest Classfication

I am a beginner in KNIME and I need to predict attribute I have some questions : 1- How can I choose the most related attribute to predict the target attribute? 2- can I choose the attributes ...
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44 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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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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26 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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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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29 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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12 views

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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4answers
135 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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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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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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52 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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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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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
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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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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
42 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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1answer
36 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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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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65 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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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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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
31 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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143 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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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 ...
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25 views

DecisionTreeClassifier for multi label classification giving outputs as single classes

I have built a DecisionTreeClassifier for multi-label classification with details given on https://scikit-learn.org/stable/modules/multiclass.html with input data in shape ...
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90 views

How to build a symptom checker and medical diagnose chat bot

I want to build a chatbot which can diagnose an illness depending upon the symptoms which are given to it. I want to show you an example scenario of how it should work; Application - A , User - U ...
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Finding optimal region of a continuous search space

I'm working on a problem in which I've got large table of data with two features and three target columns and I need to find the optimal filter parameters which theoretically would give me: 1) most ...
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Number of iterations for minimal cost complexity prunning?

I've been fiddling with weka's J48 decision tree implementation (C4.5). My goal is to implement cost complexity prunning using weakest link cut method. Basically my algorithm iteratively prunes the ...
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Wrong calculation of feature importance of decision tree in R

I trained decision tree both in python and R, but I think the way feature importance is calculated in R may be wrong. Following is the sample code which you can use to reproduce the problem. Let's say ...
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224 views

What is the differences in the Gini Index, Chi-Square, and Information Gain splitting methods?

I am looking through decision trees, and I do not understand what makes each of these methods different. Could someone explain clearly what the difference between these is? Thank you.
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201 views

Classify sensor data (multivariate time series) with Python's scikit-learn decision tree

i'm trying to apply scikit learns decision tree on the following dataset with the goal of classifying the data: sensordata: multiple .csv files every .csv file has multiple sensors (see here) each ....
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What does it mean to take the “average” of two decision trees by 'voting'

I have heard, in relation to random forest algorithm, that the algorithm will fit many decision trees and take the average of them by votes. (This is related to bagging as well) I understand what ...
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Choosing the first node in a decision tree, basic example

I'm wondering whether I'm understanding the process of choosing a node correctly and would like to see if this example makes sense. using the following data : ...
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Why can decision trees have a high amount of variance

I've heard that decision trees can have a high amount of variance, and that for a data set $D$ split into test/train the decision tree could be quite different depending on how the data was split. ...
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why do we need row sampling in random forests?

In random forests, where our estimators are decision trees, we do column (feature) sampling without replacement within an estimator, and with replacement in between estimators. This is perfectly fine ...
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86 views

How to determine number of leaves in decision tree analysis?

Would be grateful if some expert on the forum can help me understand how to decide optimum number of leaves in a decision tree analysis. I am using SAS and if I supply leaves=6 in my model then miss-...
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1answer
89 views

Not able to interpret decision tree when using class_weights

I'm working with an imbalanced dataset. I'm using a decision tree (scikit-learn) to build a model. For explaining my problem I've taken iris dataset. When I'm setting class_weight=None, I understood ...
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Compile See5 / C50 GPL Edition

See5 / C5.0 is Data Mining Tools available from rulequest I want to compile C50 for Linux, preferably for CentOS 6.x, but I am unable to compile. I have also tried on Ubuntu, but not success there as ...
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2answers
239 views

Cross Entropy vs Entropy (Decision Tree)

Several papers/books I have read say that cross-entropy is used when looking for the best split in a classification tree, e.g. The Elements of Statistical Learning (Hastie, Tibshirani, Friedman) ...
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89 views

Grid search model isn't recognized as fitted for Graphviz

I find this really weird, and the code is really straight forward. What am I doing wrong ? ...