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Questions tagged [pruning]

11 questions
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1 answer

What is Pruning & Truncation in Decision Trees?

Pruning & Truncation As per my understanding Truncation: Stop the tree while it is still growing so that it may not end up with leaves containing very low data points. One way to do this is to set a minimum number of training inputs to use on each…
Pluviophile
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Optuna Median Pruner n_warmup_steps

For Gradient Boosting Models such as XGBOOST and LGBM does n_warmup_steps in optuna.pruners.MedianPruner refer to the minimum number of folds evaluated before pruning is triggered? I.e. if number of CV folds equals 5 then n_warmup_steps=1 means…
Kjetil Haukås
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Structured and unstructured pruning for deep learning models

I was trying to understand structured and unstructured pruning techniques used for deep learning models: link 1 and link 2. To recap what I have understood that unstructured pruning is based on weight pruning however structured pruning is basically…
root
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Efficient Decision Tree Pruning

Is there an efficient way to handle pruning in Decision Tree with Python ? Currently I'm doing that: def do_best_tree(Xtrain, ytrain, Xtest, ytest): clf = DecisionTreeClassifier() clf.fit(Xtrain, ytrain) path =…
EzrielS
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cost-complexity-pruning-path with pipeline

I'm using Kaggle's titanic set. I'm using pieplines and I'm trying to prune my decision tree and for that I want the cost_complexity_pruning_path. The last line of code produces the error: ValueError: could not convert string to float: 'male' …
user5744148
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Search for redundant filters(channels) in CNN

When training a CNN one specifies in each layer the number of channels. In the input we have 1 channel for grayscale image and 3 for RGB image, and then usually the image resolution is decreased, whereas the number of channels increases (64, 128,…
spiridon_the_sun_rotator
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How to apply pruning on a BERT model?

I have trained a BERT model using ktrain (tensorflow wrapper) to recognize emotion on text, it works but it suffers from really slow inference. That makes my model not suitable for a production environment. I have done some research and it seems…
Stamatis Tiniakos
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Different Decision Tree pruning method

I am trying to learn different pruning methods for decision trees. I have put together a list of methods below. Reduced Error Pruning Cost Complexity pruning Minimum error pruning Pessimistic Error Pruning Critical Value Pruning Error Based…
Surbhi
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Difference between rpart models, one with information split the other with rpart.control

What is the difference between these two models? bankmodel <- rpart(y ~ ., data = train, method = "class", control = rpart.control(cp = 0)) info.model <- rpart(y~., data = train, parms=list(split="information")) I see one is split using the…
cocoakrispies98
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Pruning in Decision trees

Following is what I learned about the process followed during building and pruning a decision tree, mathematically (from Introduction to Machine Learning by Gareth James et al.): Use recursive binary splitting to grow a large tree on the…
Kuljeet Keshav
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Weight pruning of CNN

I was confused when i was reading about weight pruning on CNN. Is it applied for all the layers including convolutional layers or only it is done for dense layers?
root
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