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Overfitting occurs when a machine learning model performs well on training data but poorly on unseen data, often due to excessive complexity or insufficient generalization. Dropout is a regularization technique that helps mitigate overfitting by randomly "dropping out" or deactivating a fraction of neurons during training. This prevents the model from becoming overly reliant on specific neurons and promotes robustness in learning. For example, in deep learning models, a dropout rate of 0.5 ensures that 50% of neurons are deactivated in each forward pass, encouraging diverse feature representations. By leveraging dropout, neural networks become less prone to memorizing training data and improve generalization on test datasets. Why Other Options Are Incorrect :
Leprosy, also known as Hansen’s disease, is a chronic disease caused by
Treatment of defects in heredity through Genetics engineering is
Which organ have the capacity of regeneration
Which of the following pairs is incorrectly matched regarding the cause of the disease?
I) Ringworm - Virus
II) Rubella - Bacteria ...
What is the outer layer of a dental crown called?
Which antibiotic was discovered by Alexander Fleming in 1928
Which of the following organelles shows similarity to a prokaryotic cell?
Which hormone predominantly influences plant growth?
What is essential for maintaining pregnancy in women?
Which among the following is not a connective tissue?