napkinxc.measures.psdcg_at_k

napkinxc.measures.psdcg_at_k(Y_true, Y_pred, inv_ps, k=5, normalize=True)[source]

Calculate Propensity Scored Discounted Cumulative Gain (PSDCG) at 1-k places.

Parameters:

  • Y_true (ndarray, csr_matrix, list[list|set[int|str]]) – Ground truth provided as a matrix with non-zero values for true labels or a list of lists or sets of true labels.

  • Y_pred (ndarray, csr_matrix, list[list[int|str]], list[list[tuple[int|str, float]]) – Predicted labels provided as a matrix with scores or list of rankings as a list of labels or tuples of labels with scores (label, score). In the case of the matrix, the ranking will be calculated by sorting scores in descending order.

  • inv_ps (ndarray, list, dict) – Inverse propensity (propensity scores) for each label. In case of text labels needs to be a dict.

  • k (int, optional) – Calculate at places from 1 to k, defaults to 5

  • normalize (bool, optional) – Normalize result to [0, 1] range by dividing it by best possible value, commonly used to report results, defaults to True

Returns:

Values of PSDCG at 1-k places.

Return type:

ndarray