All Questions
Tagged with machine-learning decision-trees
279
questions
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Only one node generated after using decision tree model on training data set
I am trying to build a decision tree model predicting an outcome variable (named : Results) based on predictor variable. Indeed, I have applied one-hot encoding on some of the ">2 level" ...
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16
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Latest Tree-based models
What are the latest Tree-based models that are used in machine learning? Tell the new models except the old ones such as the Decision tree, Random Forest, Gradient Boosting, LightGBM, XGBoost, and ...
2
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1
answer
86
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How do I interpret probability results in conjunction with my known precision/accuracy/recall scores?
I have a Random Forest Classifier (trained with sklearn) modeling a binary data set. Here's what the configuration looks like (I've tuned it for precision intentionally):
...
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28
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Neural Network Weights - How do they know their position?
I am a copyright scholar so please forgive my ignorance.
When weights are stored external to a model what is the mechanism by which the weight knows which neuron or node in a decision tree it is ...
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40
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How to determine the optimal number of trees in Random Forest?
Here I list possible answers for mine:
Do you use the graph for OOB?
Do you use any other kind of graph?
Do you take a fixed number in default?
Do you take in consideration any research paper ...
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20
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Oblique Decision Tree HHCART algorithm explaination
I am now studying a paper about implementing oblique decision tree algorithm
https://arxiv.org/abs/1504.03415
I was wondering if any code implementation and alternative explaination, as a support ...
- 149
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131
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Optimizing decision tree
I have a question regarding the technique/technology which could be applied for the issue:
Suppose I have a rule-based tree or decision tree which predicts a variable Y based on variables A,B,C. This ...
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1
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30
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How to know which rules were applied to predict one sample in trained decision tree model?
I have trained Random Forest Regressor from sklearn. I am able to return text representation from each Decision Tree rule using tree.export_text (sklearn documentation here). But it shows rules for ...
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60
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Training Biased/Uneven Categorical Data with CatBoost, Unbalanced/Unseen Categories Handling
Summary:
I am training a discount eligibility model where the dataset represents historical data for products where people availed discounts based on simple features like product category, discount ...
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-1
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2
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148
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Recall and Precision ML models
I use decision trees for a binary classification. To evaluate the model, I use K-fold cross-validation, where k = 10.
When I run the model n times, I get a relatively constant accuracy across all ...
0
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1
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153
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Does Random Forest Regressor use subset of trees to predict value from given data sample?
I will try to draw a little context to my question from title.
I build a Random Forest Regressor from 1000 trees using sklearn. Then I exported all the decision paths along with predicted values for ...
- 15
2
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1
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336
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Difference among ID3, C4.5, C5.0
The C4.5 algorithm uses information gain ratio instead of information gain like ID3, and it also adds pruning.
What does C5.0 add more? Is there any example of code? I looked on the web but there is ...
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1
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20
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How do I use a column with data of different layers for AI?
I am working with real estate data for an ML/DL project. In the csv file there is a column in which each cell contains data like the examples below:
...
1
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1
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118
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DART algorithm implementation. Converting mathematical notation to pseudocode
I am learning how DART algorithm (https://arxiv.org/abs/1505.01866) works and I want to implement it in C#
I have the algorithm's description in mathematical notation and I don't understand most of it....
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2k
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How do the splits points in a decision tree within Random Forest are taken/selected? (Base on which criteria?)
I checked many posts to figure out how random forest (RF) learning algorithm (an ensemble of many decision trees (DT) constructed by Rain forest algorithm) within bagging select split points at each ...
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