https://www.kaggle.com/datasets/navoneel/brain-mri-images-for-brain-tumor-detection
The dataset has 253 samples, which are divided into two classes with tumor and non-tumor. The number of people with brain tumor is 155 and people with non-tumor is 98.
- The optimizer is set to Adam.
- The loss function is set to binary cross-entropy, which is used for binary classification problems.
- The evaluation criterion is set to accuracy, which is used to measure the performance of the model during training and testing.
- The batch_size parameter specifies the number of samples per gradient update.
- The epochs parameter specifies the number of iterations in the entire training dataset.
- The validation_data parameter specifies the validation data used during training.
- The model is trained for 22 epochs, which means it is repeated 22 times on the entire training dataset.
- During training, the performance of the model is evaluated based on the validation data. This helps prevent overfitting and ensures that the model generalizes well to new data.
Accuracy | Loss |
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