the accuracy of the training set is about 79%. How can I improve the accuracy of the model?
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We'd like to know how to improve the accuracy of the *Classification learner* (CL) results in Matlab R2021a. We are attempting to use (CL) to categorise Arabic speech errors into five classes, and the highest accuracy we have achieved is 79%. Including data with a size of 20000*1100 & a features vector with a size of 1100*33 Is there anything else that can be considered in order to maximize the resultant accuracy ? And is it possible to suggest a better tool to use instead of (CL) to complete this task ? Thanks a lot ,,,
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Udit06
el 29 de Nov. de 2024
Hi,
To boost classification accuracy, you can refine your feature set using PCA or LDA. Normalize your data and reduce noise for cleaner inputs. Experiment with different algorithms such as SVM, k-NN, or decision trees, and fine-tune them using cross-validation. If class imbalance is an issue, try balancing methods like oversampling or undersampling.
You can also consider using a deep learning approach like LSTM which are suitable for speech and sequence data. You can refer to the following documentations for the same:
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