I am working on a multi-class classification problem with an imbalanced dataset.
I am using ImageDataGenerator.flow_from_dataframe method. Which requires class labels to in str, list or tuple format while the class_weight argument in fit method requires a dictionary with keys in int format.
How can I implement this?
Hi @Meghansh_Bansal, First you have to calculate the class weights based on the imbalanced data. For example,
from sklearn.utils import class_weight
class_weights = class_weight.compute_class_weight('balanced', np.unique(y_train), y_train)
Then you can pass calculated class_weights to class_weight argument. For more details please refer to this document. Thank You.
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