Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [decision-trees]

For question involving decision trees in any form of AI.

46 questions
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Are decision tree learning algorithms deterministic?

Are decision tree learning algorithms deterministic? Given a fixed dataset, do they always produce a tree with the same structure? What about the random forest?
mallea
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Why does nobody use decision trees for visual question answering?

I'm starting a project that will involve computer vision, visual question answering, and explainability. I am currently choosing what type of algorithm to use for my classifier - a neural network or a decision tree. It would seem to me that, because…
The Impossible Squish
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Why isn't my decision tree classifier able to solve the XOR problem properly?

I was trying to solve an XOR problem, and the dataset seems like the one in the image. I plotted the tree and got this result: As I understand, the tree should have depth 2 and four leaves. The first comparison is annoying, because it is close to…
Pedro Paiva
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How could decision tree learning algorithms cope with imbalanced classes?

Decision trees and random forests may or not be more suited to solve supervised learning problems with imbalanced labels (or classes) in datasets. For example, see the article Using Random Forest to Learn Imbalanced Data, this Stats SE question and…
jennifer ruurs
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Decision tree: more than 2 classes, how to represent elements that are in a class vs ones that aren't?

I'm building a decision tree and would like to separate (for example) the elements that are in class 0 from those in classes 1 and 2, case in point: df = pd.DataFrame(np.random.randn(500,2),columns=list('AB')) cdf = pd.DataFrame(columns=['C']) cdf =…
Jessica Chambers
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Given a dataset with no noisy examples, is the training error for the ID3 algorithm always 0?

Given a dataset with no noisy examples (i.e., it is never the case that for 2 examples, the attribute values match but the class value does not), is the training error for the ID3 algorithm is always equal to 0?
jrk
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What makes a machine learning algorithm a low variance one or a high variance one?

Some examples of low-variance machine learning algorithms include linear regression, linear discriminant analysis, and logistic regression. Examples of high-variance machine learning algorithms include decision trees, k-nearest neighbors, and…
Posi2
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Why is the exponential loss used in this case?

I am reading the paper Tracking-by-Segmentation With Online Gradient Boosting Decision Tree. In Section 2.1, the paper says Given training examples, $\left\{\left(\mathbf{x}_{i}, y_{i}\right) \mid \mathbf{x}_{i} \in \mathbb{R}^{n}\right.$ and…
Zhang Liao
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How to calculate the entropy in the ID3 decision tree algorithm?

Here is the definition of the entropy $$H(S)=-\sum_{x \in X} p(x) \log _{2} p(x)$$ Wikipedia's description of entropy breaks down the formula, but I still don't know how to determine the values of $X$, defined as The set of classes in $S$ and…
Z. Reticulan
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Why do we use a weighted average of child entropies when we calculate information gain?

In the decision tree algorithm, why do we use a weighted average of child entropies when we calculate information gain? What is wrong about using the arithmetic mean of entropies?
Krushe
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What is the difference between Inductive Learning and Connectionist Learning?

According to what we know about inductive and connectionist learning, what is the difference between them ? For those who do not know about : Inductive Learning, like what we have in decision tree and make a decision based on amount of…
Mahdi Amrollahi
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“Outside-in” versus “Inside-out” machine learning

A little background... I’ve been on-and-off learning about data science for around a year or so, however, I started thinking about artificial intelligence a few years ago. I have a cursory understandings of some common concepts but still not much…
SuperCodeBrah
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What are possible functions assigned on decision nodes for decision tree prediction?

In Decision Tree or Random Forest, each tree has a collection of decision nodes (in which each node has a threshold value) and a class labels (or regression values). I know that threshold values are used for comparison with a corresponding feature…
user9414424
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How can I minimize the number of answers that are relevant to a machine learning model?

Problem: We have a fairly big database that is built up by our own users. The way this data is entered is by asking the users 30ish questions that all have around 12 answers (x, a, A, B, C, ..., H). The letters stand for values that we can later…
Yvan Stemmerik
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What do the values of the leaves of the decision tree represent?

This is more of a technical question rather than a practical one. I've exported a decision tree made with python/scikit learn and would like to know what the "value" field of each leaf corresponds to.
Jessica Chambers
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