torcheval.metrics.functional.click_through_rate

torcheval.metrics.functional.click_through_rate(input: Tensor, weights: Optional[Tensor] = None, *, num_tasks: int = 1) → Tensor

Compute the click through rate given a click events. Its class version is torcheval.metrics.ClickThroughRate.

Parameters:

• input (Tensor) – Series of values representing user click (1) or skip (0) of shape (num_events) or (num_objectives, num_events).
• weights (Tensor, Optional) – Weights for each event, tensor with the same shape as input.
• num_tasks (int) – Number of tasks that need weighted_calibration calculation. Default value is 1.

Examples:

>>> import torch
>>> from torcheval.metrics.functional import click_through_rate
>>> input = torch.tensor([0, 1, 0, 1, 1, 0, 0, 1])
>>> click_through_rate(input)
tensor(0.5)
>>> weights = torch.tensor([1.0, 2.0, 1.0, 2.0, 1.0, 2.0, 1.0, 2.0])
>>> click_through_rate(input, weights)
tensor(0.58333)
>>> input = torch.tensor([[0, 1, 0, 1], [1, 0, 0, 1]])
>>> weights = torch.tensor([[1.0, 2.0, 1.0, 2.0],[1.0, 2.0, 1.0, 1.0]])
>>> click_through_rate(input, weights, num_tasks=2)
tensor([0.6667, 0.4])