From 5e76c3d6b7afb4755e9238d4d1a4cc8d876cce34 Mon Sep 17 00:00:00 2001 From: c0d33ngr <106184818+c0d33ngr@users.noreply.github.com> Date: Sun, 30 Jun 2024 07:48:44 +0100 Subject: [PATCH] docs: Update model_builder.py to resolve warning in documentation build (#797) --- pymc_marketing/model_builder.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/pymc_marketing/model_builder.py b/pymc_marketing/model_builder.py index 786db671..7a0f7104 100644 --- a/pymc_marketing/model_builder.py +++ b/pymc_marketing/model_builder.py @@ -505,7 +505,7 @@ def predict( for each input row is the expected output value, computed as the mean of MCMC samples. Parameters - --------- + ---------- X_pred : array-like if sklearn is available, otherwise array, shape (n_pred, n_features) The input data used for prediction. extend_idata : Boolean determining whether the predictions should be added to inference data object. @@ -553,7 +553,7 @@ def sample_prior_predictive( Sample from the model's prior predictive distribution. Parameters - --------- + ---------- X_pred : array, shape (n_pred, n_features) The input data used for prediction using prior distribution. samples : int @@ -605,7 +605,7 @@ def sample_posterior_predictive( Sample from the model's posterior predictive distribution. Parameters - --------- + ---------- X_pred : array, shape (n_pred, n_features) The input data used for prediction using prior distribution.. extend_idata : Boolean determining whether the predictions should be added to inference data object. @@ -687,7 +687,7 @@ def predict_posterior( Generate posterior predictive samples on unseen data. Parameters - --------- + ---------- X_pred : array-like if sklearn is available, otherwise array, shape (n_pred, n_features) The input data used for prediction. extend_idata : Boolean determining whether the predictions should be added to inference data object.