Questions tagged [decision-tree]

For question involving decision trees in any form of AI.

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How can I classify instances into two categories and then into sub-categories, when the number of features is high?

I'm working with a problem where I have a lot of variables for different cases of different users. Depending on the values of the different variables of a concrete user in a concrete case, the ...
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1answer
27 views

Feature extraction timeseries, model compatibility

I've got a timeseries with sensor data (e.g. accelerometer and gyroscope). I now want to extract the activity out of it (e.g. walking, standing, driving, ...). I Followed this Jupyter Notebook. But ...
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1answer
58 views

How does the decision tree implicitly do feature selection?

I was talking with an ex-fellow worker and he told me that the decision tree implicitly applies a feature selection. He told me that the most important feature is higher in the tree because of the ...
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1answer
50 views

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 ...
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1answer
56 views

Is it possible to create a decompiler using AI?

I am trying to decode a compiled file to source code and I am failing. I want to know whether an AI based decompilation is possible for a compiled files? Is it possible to create a decompiler using a ...
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1answer
54 views

“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 ...
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1answer
39 views

Can the C4.5 algorithm learn a GOAP model?

Goal-oriented action planning (GOAP) is a well-known planning technique in computer games. It was introduced to control the non-player characters in the game F.E.A.R. (2005) by creating an abstract ...
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13 views

How to gauge importance in random forest when there is overlap between variables

I have a dataset where I'm trying to gauge the importance of certain drivers (X and Y) over various time periods. I'd like to look at the importance of certain ranges of times, which will overlap with ...
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1answer
34 views

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 ...
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1answer
22 views

At which point we have to stop post pruning in decision tree?

Post pruning is start from downward discarding subtree and include leaf node performance. so what is the best point or condition of the tree where we have to stop further pruning.
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232 views

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?
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43 views

What kind of decision rule algorithm is usable in this situation?

I am trying to write an AI to a game, where there is no real adversary. This means, that only the AI player has choices in which move to perform, his opponent may or may not react to the move the AI ...
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1answer
106 views

Why KNN, Decision Trees, etc have a high variance?

Some examples of low-variance Machine Learning algorithms include Linear Regression, Linear Discriminant Analysis and Logistic Regression. Examples of high-variance Machine Learning algorithms ...
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1answer
44 views

How many trees should be generated in a random forest?

What are ways of determining the number of trees to be generated in a random forest algorithm?
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116 views

Decision making systems applications

Machine learning and data science are mainly made for processing large amounts of data nowadays, for example - a multitude of pictures. But do these fields have some applications in the decision ...
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2answers
68 views

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). ...
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1answer
155 views

Why was Go a harder game for an AI to master than Chess?

AI became superior to the best human players in chess around 20 years ago (when the 2nd Deep Blue match concluded). However, it took until 2016 for an AI to beat the Go world chess champion, and this ...
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1answer
79 views

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: ...
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1answer
155 views

Scikit learn: Decision tree data meaning

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....
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1answer
165 views

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, and am currently choosing what type of algorithm to use for my classifier - a neural net, or a ...
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1answer
518 views

What is the intuition behind the entropy formula used in the ID3 algorithm?

What is the intuition behind the following entropy formula used in the ID3 algorithm? $$ \text{info}(D) = -\sum_{i=1}^m p_i \log_2(p_i) $$