machine-learning artificial-intelligence classification adaboost

Weak Classifier

I am trying to implement an application that uses AdaBoost algorithm. I know that AdaBoost uses set of weak classifiers, but I don't know what these weak classifiers are. Can you explain it to me with an example and tell me if I have to create my own weak classifiers or I'm suppoused to use some kind of algorithm?

Solution

When I used AdaBoost, my weak classifiers were basically thresholds for each data attribute. Those thresholds need to have a performance of more than 50%, if not it would be totally random.

Here is a good presentation about Adaboost and how to calculate those weak classifiers: https://user.ceng.metu.edu.tr/~tcan/ceng734_f1112/Schedule/adaboost.pdf

How to fix the learning-rate for Huggingface´s Trainer?
Roboflow Vs. Darknet for generating weight file and creating the model
What is the difference between backpropagation and reverse-mode autodiff?
Load Registered Component in Azure ML for Pipeline using Python sdk v2
classifiers in scikit-learn that handle nan/null
Encoding two categorial data present in same dataset in Deep learning
Machine learning in q/kdb+
Why do the sensitivity (recall) values differ between classification_report and precision_recall_fscore_support in a loop?
How do you specify the bfloat16 mixed precision with the Intel Extension for PyTorch?
mlflow doesn't autolog artifacts while logging images
Choosing top k models using GridSearchCV in scikit-learn
Calculating pairwise distances between entries in a `torch.tensor`
Reusing a feature to split regression decision tree's nodes
Fine tuning LayoutLmv3 using Cord-V2 dataset
What does model.eval() do in pytorch?
ElasticNetCV in Python: Get full grid of hyperparameters with corresponding MSE?
Why is the accuracy for my Keras model always 0 when training?
Polars - issues with performance - attempting to create a new dataframe per row
Keras model.export() fails because of NoneType shapes in model
Meta-feature analysis: split data for computation on available memory
Single-headed transformer model, output and target tensor sizes don't match
How to add the bounding box values to the labels text files during prediction with a trained YOLO-V8 instance segmentation model?
How to calculate correlation of colours in a dataset?
Convert array of indices to one-hot encoded array in NumPy
Import custom prediction routine to vertex AI pipeline
what is the difference between bigram and unigram text features extraction
How to map the results of Principal Component Analysis back to the actual features that were fed into the model?
How to calculate optimal batch size?
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample
Center an image and adding a background at export