Neural networks are advanced computational models that mimic the human brain's structure, enabling them to capture and model complex, non-linear relationships between inputs and outputs. They consist of layers of perceptrons (neurons) that process inputs through weighted connections.
Machine learning often involves optimization problems that aim to minimize or maximize a particular function, known as a loss function. Two of the most common loss functions are square loss and log loss. In this note, we'll delve into log loss by exploring a probability-based example and provide the mathematical foundations for understanding it better.
线性模型旨在将目标值预测为输入特征的线性组合。通常表示为：
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| Model | Mathematical Expression | Description |
在机器学习中，模型评估是理解模型性能的关键一步。此过程中的两个关键概念是假设和损失函数。