Pragmatic Programming Techniques

Pragmatic Programming Techniques

In classical prediction use case, the predicted output is either a number (for regression) or category (for classification).  A set of training data (x, y) where x is the input and y is the labeled output is provided to train a parameterized predictive model.

• The model is characterized by a set of parameters w
• Given an input x, for the model predicts y_hat = f(x; w) for regression, or the model predicts the probability of each possible class for classification
• Define a Lost function L(y, y_hat) for regression, or L(y, P(y=a | x), P(y=b | x) ...), find the parameters w to minimize L

This problem is typically view as an optimization problem, and use gradient descent approach to solve it.

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