From 059a3afede0ec6d6665e8f9253aea1e946f94181 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Julian=20Sp=C3=A4th?= Date: Wed, 16 Oct 2019 18:51:52 +0200 Subject: [PATCH] Remove timeline parameter. It is not really needed here --- random_survival_forest/SurvivalTree.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/random_survival_forest/SurvivalTree.py b/random_survival_forest/SurvivalTree.py index 2cbcc07..ad9650a 100644 --- a/random_survival_forest/SurvivalTree.py +++ b/random_survival_forest/SurvivalTree.py @@ -7,14 +7,13 @@ class SurvivalTree: prediction_possible = None - def __init__(self, x, y, f_idxs, n_features, timeline, unique_deaths=3, min_leaf=3, random_state=None): + def __init__(self, x, y, f_idxs, n_features, unique_deaths=3, min_leaf=3, random_state=None): """ A Survival Tree to predict survival. :param x: The input samples. Should be a Dataframe with the shape [n_samples, n_features]. :param y: The target values as a Dataframe with the survival time in the first column and the event. :param f_idxs: The indices of the features to use. :param n_features: The number of features to use. - :param timeline: The timeline used for the prediction. :param unique_deaths: The minimum number of unique deaths required to be at a leaf node. :param min_leaf: The minimum number of samples required to be at a leaf node. A split point at any depth will only be considered if it leaves at least min_leaf training samples in each of the left and right branches. @@ -23,7 +22,6 @@ def __init__(self, x, y, f_idxs, n_features, timeline, unique_deaths=3, min_leaf self.y = y self.f_idxs = f_idxs self.n_features = n_features - self.timeline = timeline self.min_leaf = min_leaf self.unique_deaths = unique_deaths self.random_state = random_state